Asian Digital Libraries. Looking Back 10 Years and Forging New Frontiers

Our multicultural societies in a globalized context offer the opportunity to forge new frontiers in digital libraries. Focusing on the cultural diversity of the Asian region, this paper examines what should be digitized, who should be involved in the digitization efforts, and what access issues need to be considered. More specifically, documenting the experiences of the Asian diaspora and ethnic minorities will be discussed, engaging critical theories and multicultural scholarship. By problematizing the cultural production of digital libraries as an act of nostalgia, of inclusion and exclusion, and of racial, social and sexual differentiation, we can unpack the role that digital libraries play in the creation of communities in our imaginary and in the perception of space and place from those objects we select to digitize. The paper concludes with a call for decentering digital libraries and digitizing the “Other” as an act of empowerment and representation.

If the network has become the computer, search is in the process of becoming its interface. This transformation impacts the design of future digital libraries. On the content side, innovations in contextual search are driving a new precision level compared to existing search paradigms inherited from the web. On the user side, search will have an equally profound impact. Closed loop designs connecting social computing and search is transforming libraries from a static repository to a dynamic learning and collaboration space.

Together with a number of national libraries, the Internet Archive committed itself in 2003 to international collaboration to create open source tools and standardized formats for web archiving. This project was motivated by our experience as home to over 100 billion archived web resources dating back to 1996, and as a partner to memory institutions building thematic web archives. Resulting tools include the

Heritrix

archival web crawler/harvester, the

Wayback

archive browsing service, and the

NutchWAX

archive full-text index and query utilities. A standard ingest/archival format for web resources called

WARC

has also been developed. Software with full source code is free to download and reuse, and organizations worldwide have adopted and contributed to these tools. Working with large collections remains a challenge, and the web itself is constantly growing and changing, so we continue to seek international cooperation to expand and improve this web archive tool set.

Kristine Hanna, Director of Web Archiving Services at Internet Archive, will discuss the significance of web archiving, the challenges libraries, archives and memory institutions face in the digital age, as well as some of tools and best practices currently in use to create a successful web archiving strategy.

The Internet Archive, located at http://www.archive.org/index.php on the web, has been involved in web archiving since 1996 when the organization was founded as an internet library to provide permanent access for researchers, historians and the general public to the world’s cultural artifacts. Additionally the web group at the Archive http://wa.archive.org/ works with institutions to created focused collections through crawling services and Archive-It, a web based application.

The Internet Archive is a founding members of the IIPC (International Internet Preservation Consortium http://netpreserve.org/about/index.php, and we work closely with national libraries and archives from around the globe to develop open source tools and document best practices for web archiving.

The talk presents an interpretation of the evolution of the events and trends in the information access area. Focusing mainly on the last twenty years, particular attention is payed to the digital library system which needs to be envisaged and designed to support the end user in accessing relevant and interesting documents.

This presentation shows how the joint efforts of the national libraries of Europe over the past 20 years have paved the way for the creation of a European Digital Library; currently a collaborative platform for European museums, archives and libraries, but in future also a webservice for end-users to discover Europe’s heritage on an unprecedented scale. This presentation sets out the recipe for the first construction phase (2007-2008) and discusses the ingredients that are needed to build an operational European Digital Library from 2009 onwards.

Hospital portals are becoming increasingly popular since they play an important role to provide, acquire and exchange information. Knowledge management (KM) mechanisms will be useful to hospitals that need to manage health related information, and to exchange and share information with their patients and visitors. This paper presents a comprehensive analysis of knowledge management mechanisms used by 20 hospital portals from North America and Asia to access, create and transfer knowledge. We developed a systematic and structured approach to evaluate how well the portals captured and delivered information to patients and visitors about the hospitals’ business processes, products, services, and customers from the perspective of three KM mechanisms (i.e. knowledge access, knowledge creation and knowledge transfer). Our results show that our selected hospital portals provided varying degrees of support for these KM mechanisms.

We describe the Image Tagger system – a web-based tool for supporting collaborative image indexing by students. The tool has been used in three successive graduate-level classes on content representation. To fully satisfy the class’ requirements and provide support for student indexing activities, it was designed and developed iteratively in accordance with the feedback and suggestions from the students as well as the instructor. The tool was well received by most students. They expressed a positive opinion toward collaboration support and thought it enhanced the overall learning experience in the class’ image indexing project.

In the context of an ongoing collaboration conducted between DELOS, the European Network of Excellence on Digital Libraries, and The European Library, we discuss how both the analysis of the Web log data of The European Library service and a user study can contribute to the personalization of services for such a system.

Using Nielsen’s well-established Heuristic Evaluation normally used for gathering

qualitative

feedback, this paper describes a user study conducted on the National Library Board’s Digital Library (NLBDL) in Singapore to gather

quantitative

feedback on users’ perceptions regarding compliance/violation of design heuristics implemented, and draw recommendations for design refinement.

The National Taiwan University Library has built a digital library of historical documents about Taiwan. The content is unique in that it covers about 80% of all primary Chinese historical materials about Taiwan before 1895, and that they are all available in searchable full text, in addition to metadata. To make these materials more accessible to the research community, we have developed, in addition to full-text search and retrieval, a concept of regarding the set of documents retrieved by a query as a sub-collection, and have designed post-query classification methods to help users find the inter-relationships among documents and the collective meaning of a sub-collection. We have also developed techniques for term extraction for old Chinese and a data format for representing governmental structures. We hope that our system will help advance research in Taiwanese history, and will set a model for other similar endeavor.

Contemporary digital libraries and archives of ethnological information focus mainly on document based storage and access methods for their data. However, our archive is designed to manage smallest pieces of information and can enable ethnologists not only to easily store and access their material, but also to derive new knowledge by combining existing data. In this paper, we present the first steps in building a digital archive for paper slips with ethnological contents from the 19th and the beginning of the 20th century. Along with the architectural and accessibility aspects of the

WossiDiA

system, we describe enhancements for efficient retrieval and for supporting modifications to access structures.

This study seeks to develop an automatic method to identify product review documents on the Web using the snippets (summary information that includes the URL, title, and summary text) returned by the Web search engine. The aim is to allow the user to extend topical search with genre-based filtering or categorization. Firstly we applied a common machine learning technique, SVM (Support Vector Machine), to investigate which features of the snippets are useful for classification. The best results were obtained using just the title and URL (domain and folder names) of the snippets as phrase terms (n-grams). Then we developed a heuristic approach that utilizes domain knowledge constructed semi-automatically, and found that it performs comparatively well, with only a small drop in accuracy rates. A hybrid approach which combines both the machine learning and heuristic approaches performs slightly better than the machine learning approach alone.

It is necessary to provide personalized information service for users through the enormous volume of information on the web. Collaborative filtering is the most successful recommender system technology to date and is used in many domains. Unfortunately collaborative filtering is limited by the high dimensionality and sparsity of user-item rating matrix. In this paper, we propose a new method for applying semantic classification to collaborative filtering. Experimental results show the high efficiency and performance of our approach, compared with tradition collaborative filtering algorithm and collaborative filtering using K-means clustering algorithm.

With the spread of the digital library and the web, users can obtain a wide variety of information, and also can access novel content. In this environment, finding useful information from a huge amount of available content becomes a time consuming process. In this paper, we focus on user modeling for personalization to recommend content relevant to user interests. We exploit the data mining techniques for identifying useful and meaningful patterns of users. Each user model, collectively called PTP (Personalized Term Pattern), is represented as both interest patterns and disinterest patterns. We present empirical experiments using

NSF research award

datasets to demonstrate our approach and evaluate performance compared with existing methods.

With the recent advancement of the Semantic Web, researchers are now considering developing ontology-based digital librarires for the sake of efficient information sharing, exchanging and retrieval. In addition, fuzzy queries have been also introduced to help readers to specify their queries more precisely when searching information in digital librarires. In this paper, we first propose an architecture that enables multiple digital libraries to collaborate in the Semantic Web environment. Then we discuss using fuzzy ontology to represent uncertain information in digital libraries and fuzzy queries for retrieving information from fuzzy ontology. An illustrative system is then developed for experiment purpose. Performance of our system is also evaluated and analyzed.

With the rapid emergence and proliferation of Internet and the trend of globalization, a tremendous amount of textual documents written in different languages are electronically accessible online. Poly-lingual text categorization (PLTC) refers to the automatic learning of a text categorization model(s) from a set of preclassified training documents written in different languages and the subsequent assignment of unclassified poly-lingual documents to predefined categories on the basis of the induced text categorization model(s). Although PLTC can be approached as multiple independent monolingual text categorization problems, this naïve approach employs only the training documents of the same language to construct a monolingual classifier and fails to utilize the opportunity offered by poly-lingual training documents. In this study, we propose a feature reinforcement approach to PLTC that takes into account the training documents of all languages when constructing a monolingual classifier for a specific language. Using the independent monolingual text categorization (MnTC) technique as performance benchmarks, our empirical evaluation results show that the proposed PLTC technique achieves higher classification accuracy than the benchmark technique does in both English and Chinese corpora.

A prototype morphological analyzer for the south Indian language of Kannada is presented in this work. The analyzer is based on Finite state machines and can handle 500 distinct Noun and Verb stems of Kannada. The morphological analyzer can simultaneously serve as a stemmer, part of speech tagger and spell checker and hence it becomes a very efficient tool for content management.

The concept of semantic similarity is an important element in many applications such as information extraction, information retrieval, document clustering and ontology learning. Most of the previous works regarding semantic similarity measures have been traditionally defined between words or concepts (i.e. word-to-word similarity), thus ignoring the text or sentence that the concepts participate. Semantic text similarity was made possible with the availability of resources in the form of semantic lexicon such as the WordNet for English and GermaNet for German. However, for languages such as Malay, text similarity proved to be difficult due to the unavailability of similar resources. This paper, however, describe our approach for text similarity in Malay language. We used a preprocessed Malay dictionary and the overlap edge counting based method to first calculate the word-to-word semantic similarity. The word-to-word semantic similarity measure is then used to identify the semantic sentence similarity using a modified approach for English language. Results of the experiments are very encouraging, and indicate the potential of semantic similarity measure for Malay sentences.

A growing number of people are using the Web to access English-language resources, among other things. In Asian countries, for example, many people want access to English texts. Many Asians are not as competent reading English as they may be in the intellectual content of their domain. The problem of accessibility to English texts is significant simply because of the number of people involved. The problems for second language English readers are similar to those for many dyslexic first language readers. We propose a descriptive model that supports adaptability of texts for the benefit of such people based on FRBR and AccessForAll standards.

In this paper we introduce a system that collects English-Japanese translation document pairs from the Web that are relevant to subject keywords specified by the user. The system, QRselect, is specifically designed to meet the needs of online volunteer translators who, in the process of translation, want to refer to a small and specific set of translation document pairs which are relevant to what they are translating. A system which collects relevant existing translated documents and makes them available for reference in the translation process will therefore greatly help these translators. Against this backdrop, we developed a prototype translated document collection system and evaluated its performance. We also examined the users’ role in improving the system.

Digitizing ancient books, especially those related to the humanities, is practiced in many countries. The number of full-text databases in the humanities is increasing. Studies have shown that ancient books are important resources for humanities scholars and researchers. However, comparatively little research has been done concerning the use of those databases. Thirty graduate students majoring in Chinese Literature or History were interviewed in this study. This study attempts to answer the following questions: How do interviewees use the databases? Do they encounter any problems? What do they have to say concerning ancient books in digital or paper form? The results show that humanities graduate students use ancient books databases to locate information concerning their research interests. Most of them are satisfied with the search functions and feel that the databases are convenient to use. However, they comment that the coverage, quality, and search interface could be improved upon. As well, a few graduate students suggest that links to related resources should be added. They state that they do not totally rely upon the databases and continue to use paper sources.

The increasing number of users and the diffusion of

Digital Libraries (DLs)

has increased the demand for newer and improved systems to give better assistance to the user during the search of resources in collections managed by

Digital

Library

Systems

(

DLSs

). In this perspective, the annotations made on documents offer an interesting possibility for improving both the user experience of the DLS and the retrieval performance of the system itself. However, while different approaches based on annotations have been proposed, they still lack a full experimental evaluation, mainly because an experimental collection with annotation is missing. Therefore, this paper addresses the problem of setting an adequate experimental test-bed for DL search algorithms which exploit annotations, and discusses a flexible strategy for creating test collections with annotated documents.

Fair use is a difficult problem to implement in DRM systems due to its vagueness and uncertainty. We propose a fair use mechanism based on

rights assertion

without limitation,

audit logging

and

misuses trigger

, which brings a fair use mechanism nearer to offline world than that of existing DRM systems.

In this paper, we propose an ontology-based metadata integration methodology for the cultural heritage domain. The proposed real - world approach considers an integration architecture in which CIDOC/CRM ontology acts as a mediating scheme. In this context, we present a mapping methodology from Encoded Archival Description (EAD) and Dublin Core (DC) metadata to CIDOC/CRM, and discuss the faced difficulties.

The purpose of this paper is to raise arguments to support the proposal that we should promote the discussion of the Digital Library in a structured way, aligned with the emerging perspective of the Enterprise Architecture. In this sense, the Digital Library practitioners should be motivated to give more emphasis to the need to better integrate its efforts and body of knowledge with the more generic area of Information Systems, where important concepts, regulations and good practices have been emerging, defined by authorities, the industry and the multiple stockholders of each specific scenario. Concluding, it is time for the Digital Library to mature by recognizing that it is, simply, a case of an Information System, which is specific only in what concerns the requirements derived of its specific business goals.

The paper presents a multimedia database model accounting for the representation of documents, collections and the associated metadata. Appropriate structures are provided for descriptive metadata and for metadata resulting from automatic content analysis. The model is based on the identification and unification of the main concepts in the archival standards and the audiovisual area.

The main features of the model, designed to support multimedia database applications, are the integration of descriptive and content analysis metadata, the association of metadata to collections as well as to items, the extensibility with respect to the inclusion of new descriptors and the support to several retrieval modes. The MetaMedia application development platform, based on the model, has been used to support the construction of a historic documentation collection where a common web interface provides collection administrators, metadata creators and visitors a multi-faceted view of the repository.

We propose in this paper to integrate the semantic description of the image and the relational characterization of its components through an architecture which follows a sharp process for generating image index and query representations and computing their correspondence. This architecture relies on an expressive representation formalism handling high-level image descriptions and a conceptual query framework in an attempt to operate image indexing and retrieval operations beyond keyword-based and loosely-coupled state-of-the-art systems. At the experimental level, we evaluate its retrieval performance through recall and precision indicators on a test collection of 2500 color photographs.

In this paper, we discuss current issues and future trends on intellectual properties of digital libraries by interpreting legal concepts in engineering manner as a reference to Asia-Pacific DL researchers and practitioners. First, we discuss problems on copyright entities in digital libraries and patent objects in their retrieval mechanisms. Second, we formulate the conditions of copyrightability on the multimedia databases as digital libraries and the patentability on the parameter setting components in retrieval mechanisms. Third, we discuss a new direction for protecting numerical parametric information as trade secret embedded in the patentable parameter setting components.

Video and text-news content have recently been broadcast on TV, newspapers, and the Internet. Although video content on out-of-date news is of little value for viewing, it can be considered to have value by comparing it to related content. Repeated news should especially be compared, e.g., the Olympic games and international expositions. We propose a method of retrieving comparison content based on the order of news elements. It is composed of two parts. The first is an analysis of news content that someone is browsing. The second is the automatic generation of queries for retrieving content on comparison news.

In this paper, an adaptive tool for providing suggestions during the information search process is presented. The tool uses case-based reasoning techniques to find the most useful suggestions for a given situation by comparing them to a case base of previous situations and adapting the solution. The tool can learn from user participation.

A small, preliminary evaluation showed a high acceptance of the tool, even if improvements are still needed.

XML information retrieval (XML-IR) systems search for relevant document fragments in XML documents for given queries. In top-

k

search, users control the size of output by an integer

k

. In XML-IR, however, each output element varies widely in size. Consequently, total output size of top-

k

elements is uncontrollable by simply giving an integer

k

. In addition, search results may have nesting elements. If a system orders result elements simply by their relevance, we may browse the same content more than once due to the nestings. To handle these problems, we propose a new ranking method that enables us to browse search results of XML-IR systems efficiently by introducing the concepts of

benefit

and

reading effort

. We also propose an evaluation metrics based on

benefit

and

reading effort

, and compared the metrics with existing XML-IR metrics by experiments.

In this study, we performed a comprehensive evaluation of pseudo-relevance feedback technique for automatic query expansion using OHSUMED test collection. The well-known term sorting methods for the selection of expansion terms were tested in our experiments. We also proposed a new term reweighting method for further performance improvements. Through the multiple sets of test, we suggested that local context analysis was probably the most effective method of selecting good expansion terms from a set of MEDLINE documents given enough feedback documents. Both term sorting and term reweighting method might need to be carefully considered to achieve maximum performance improvements.

Most of the previous works that disambiguate personal names in Web search results often employ agglomerative clustering approaches. In contrast, we have adopted a semi-supervised clustering approach in order to guide the clustering more appropriately. Our proposed semi-supervised clustering approach is novel in that it controls the fluctuation of the centroid of a cluster, and achieved a purity of 0.72 and inverse purity of 0.81, and their harmonic mean

F

was 0.76.

Over the last years, digital preservation has become a particularly active research area. While several initiatives are dealing with the preservation of standard document formats, the challenges of preserving multimedia objects and pieces of electronic art are still to be tackled. This paper presents the findings of a pilot project for preserving born-digital interactive multimedia art. We describe the specific challenges the collection poses to digital preservation and the results of a case study identifying requirements on the preservation of interactive artworks.

Many experiments and studies have been conducted on the application of FRBR as an implementation model for bibliographic databases, in order to improve the services of resource discovery and transmit better perception of the information spaces represented in catalogues. One of these applications is the attempt to identify the FRBR work instances shared by several bibliographic records. In our work we evaluate the applicability to this problem of techniques based on string similarity, used in duplicate detection procedures mainly by the database research community. We describe the particularities of the application of these techniques to bibliographic data, and empirically compare the results obtained with these techniques to those obtained by current techniques, which are based on exact matching. Experiments performed on the Portuguese national union catalogue show a significant improvement over currently used approaches.

Social bookmark services like

del.icio.us

enable easy annotation for users to organize their resources. Collaborative tagging provides useful index for information retrieval. However, lack of sufficient tags for the developing documents, in particular for new arrivals, hides important documents from being retrieved at the earlier stages. This paper proposes a spreading activation approach to predict social annotation based on document contents and users’ tagging records. Total 28,792 mature documents selected from

del.icio.us

are taken as answer keys. The experimental results show that this approach predicts 71.28% of a 100 users’ tag set with only 5 users’ tagging records, and 84.76% of a 13-month tag set with only 1-month tagging record under the precision rates of 82.43% and 89.67%, respectively.

Mobile tagging is an extension of social tagging that allows users to associate location-sensitive information with physical objects in the real world. This paper presents MoTag, a mobile tagging application that is used to help people with disabilities share up-to-date accessibility information about buildings and other physical structures to help them navigate their environment. MoTag integrates with G-Portal, a geospatial digital library for storing, managing and retrieving tags.

In the age of Web 2.0, users are increasingly familar with social tagging or bookmarking where comments and ratings are added by users to objects on the web for public consumption. Such comments and ratings are represented in bookmarks which can be used for information or opinion sharing, user interest discovery, and content recommendation. In this paper, we investigate social bookmarking in digital libraries and derive the design requirements for digital library incorporating social bookmarking. Instead of implementing social bookmarking functions in digital library systems from ground zero, we have chosen to explore the possibilities of integrating pre-existing digital library systems with pre-existing social bookmarking systems, and to derive a feasible system architectural design. We also present a case study where

G-Portal

, a geography digital library system, is integrated with

Scuttle

, an open source social bookmarking system.

With an exponential growth of Weblogs (or blogs), many blog directories have appeared to help users to locate topical blogs. As tags are commonly used to describe blogs, we study the effectiveness of tags in blog classification. Compared with titles and descriptions, our experiments, using 24,247 blogs, showed that tags could lead to better classification accuracy. It is interesting to observe that more tags did not necessarily lead to better classification accuracy. To better describe blogs, we have also proposed a tag expansion algorithm that assigns a blog more tags that are often co-occur with those already associated with the blog. Our experiments showed that tag expansion helped to improve the recall of blog classification with the price of precision degradation.

We present a keyphrase extraction algorithm for scientific publications. Different from previous work, we introduce features that capture the positions of phrases in document with respect to logical sections found in scientific discourse. We also introduce features that capture salient morphological phenomena found in scientific keyphrases, such as whether a candidate keyphrase is an acronyms or uses specific terminologically productive suffixes. We have implemented these features on top of a baseline feature set used by Kea [1]. In our evaluation using a corpus of 120 scientific publications multiply annotated for keyphrases, our system significantly outperformed Kea at the

p

 < .05 level. As we know of no other existing multiply annotated keyphrase document collections, we have also made our evaluation corpus publicly available. We hope that this contribution will spur future comparative research.

This paper describes our efforts to develop a toolset and process for automated metadata extraction from large, diverse, and evolving document collections. A number of federal agencies, universities, laboratories, and companies are placing their collections online and making them searchable via metadata fields such as author, title, and publishing organization. Manually creating metadata for a large collection is an extremely time-consuming task, but is difficult to automate, particularly for collections consisting of documents with diverse layout and structure. Our automated process enables many more documents to be available online than would otherwise have been possible due to time and cost constraints. We describe our architecture and implementation and illustrate the effectiveness of the tool-set by providing experimental results on two major collections DTIC (Defense Technical Information Center) and NASA (National Aeronautics and Space Administration).

Syllabi are important documents created by instructors for students. Gathering syllabi that are freely available, and creating useful services on top of the collection, will yield a digital library of value for the educational community. However, gathering and building a repository of syllabi is complicated by the unstructured nature of syllabus representation and the lack of a unified vocabulary for syllabus construction. In this paper, we propose an intelligent approach to automatically annotate freely-available syllabi from the Web to benefit the educational community through supporting services such as semantic search. We discuss our detailed process for converting unstructured syllabi to structured representations through entity recognition, segmentation, and association. Our evaluation results demonstrate the effectiveness of our extractor and also suggest improvements. We hope our work will benefit not only users of our services but also people who are interested in building other genre-specific repositories.

In today’s knowledge-intensive engineering environment, information management is an important and essential activity. However, existing researches of Engineering Information Management (EIM) mainly focused on numerical data such as computer models and process data. Textual data, especially the case of free texts, which constitute a significant part of engineering information, have been somewhat ignored, mainly due to their lack of structure and the noisy information contained in them. Since summarization is a process to distill important information from source documents and at the same time remove irrelevant and redundant information, it could address the obstacles for handling textual data in EIM. Moreover, text summarization could address the increasing demand to integrate information from multiple documents and reduce the time in acquiring useful information from massive textual data in the engineering domain. This paper discusses in detail the need to apply text summarization in EIM and introduces a case study in summarizing multiple online customer reviews.

This paper describes the PENG project that integrates personalized push and pull technologies to access relevant information. PENG integrates several key tasks, including personalized filtering, retrieval, and presentation of multimedia news, into a single system. In this paper we provide an overview of PENG, describing our approach to constructing a dedicated retrieval and content management system for a specific user group. We also report critically on the results of a user and task based evaluation.

This paper proposes a system for realizing a new children’s reading environment in a library. Conventional libraries establish children’s rooms for supporting children’s activities of reading printed picture books. The collections there, however, are often biased in content and limited in number, and children are usually not satisfied with them. When the entire collection becomes large, it occurs that younger children cannot effectively search that collection. Similar search problems also exist in children’s digital libraries. We have designed a system called BrowsReader with the purpose of realizing a new environment, where children can browse in a large virtual bookshelf and can easily find the digitized and/or printed picture books that they are interested in. A user study was conducted to test the effectiveness of the system.

This work investigates the potential of applying a suite of visualisation for query processing in a desktop search environment. While each of these visualizations may not be totally new on its own, we have attempted to add value to each one by endowing it with useful features, and to seamless integrate them to allow easy switching of views, thereby providing the novelty in this work to create a potentially useful means to process search results and carry out query refinements and exploration. These visualisations include a List View, Tree View, Map View, Bubble View, Tile View and Cloud View. A first evaluation was undertaken by 94 M.Sc. participants to gauge the system’s potential usefulness and to detect usability issues with its interface and graphical presentations. The evaluation results were encouraging and showed that these views to be both effective and useful on the whole, and support the research premise that a combination of integrated visualisations will result in a more effective search tool.

DIGMAP is a project to find solutions for digital libraries scenarios focused on digitised historical maps. The main service will reuse metadata from European national libraries and other relevant third party metadata sources to provide discovery and access to contents. This will also include a proof of concept of a scenario of reusing and enriching these metadata by automatic processes that will try to extract relevant indexing information from the images of the digitised maps, as well as from any kind of associated text.

SMS or short messaging service is a form of text messaging used extensively throughout the world. It is a cheap and mobile form of communication but there is limited research into its library use. Using Internet search techniques and content analysis, this research investigated how libraries use SMS. Fifty libraries with English language websites were found to be using SMS and were divided evenly between academic and public, with two national libraries. They spread over fourteen countries with the United Kingdom having the most libraries using the technology. Usage was mainly in the circulation area, particularly reserves. Some libraries offered reference services. Cost and complexity varied, with some libraries offering examples of possible future use. Suggestions are made as to the importance of libraries helping each other in implementing SMS.

Topic detection and analysis is very important to understand academic document collections. By further modeling the influence among the topics, we can understand the evolution of research topics better. This problem has attracted much attention recently. Different from the existing works, this paper proposes a solution which discovers hidden topics as well as the relative change of their intensity as a first step and then uses them to construct a module network. Through this way, we can produce a generalization module among different topics. In order to eliminate the instability of topic intensity for analyzing topic changes, we adopt the piece-wise linear representation so that we can model the topic influence accurately. Some experiments on real data sets validate the effectiveness of our proposed method.

Digital Libraries represent semantically rich collections of digital documents. Ontology-based information retrieval systems capture semantic relations for providing value added information services. Deviating from the regular approach of developing ontologies on the basis of domain knowledge, the present paper puts forward a novel method for developing ontologies from the semantic information available in the titles of digital documents. Such an approach gathers significance due to its simplicity in ontology development process. To examine the same, the study considered the case of Agricultural Electronic Theses and Dissertations (ETDs) present in Vidyanidhi Digital Library. The study resulted in the development of Indian Agricultural Research domain ontology, which was used for developing ontology-based information retrieval system. This paper while describing the methodology followed for developing the ontology presents the technical details of the developed system.

There are huge numbers of documents in digital libraries. How to effectively organize these documents so that humans can easily browse or reference is a challenging task. Existing classification methods and chronological or geographical ordering only provide partial views of the news articles. The relationships among news articles might not be easily grasped. In this paper, we propose a near-duplicate copy detection approach to organizing news archives in digital libraries. Conventional copy detection methods use word-level features which could be time-consuming and not robust to term substitutions. In this paper, we propose a sentence-level statistics-based approach to detect near-duplicate documents, which is language independent, simple but effective. It’s orthogonal to and can be used to complement word-based approaches. Also it’s insensitive to actual page layout of articles. The experimental results showed the high efficiency and good accuracy of the proposed approach in detecting near-duplicates in news archives.

Dictionary is an efficient management of large sets of distinct strings in memory. It has significant influence on Natural Language Process, Information Retrieval and other areas. In this paper, we propose an efficient dictionary mechanism, which is suitable for Double-Byte coding languages. Compared with other five popular dictionary mechanisms, this mechanism performs the best of all. It improves the search performance greatly and reduces the complexity of the construction and maintenance of the dictionary. It can be well applied in large-scale and real-time processing systems. Since Unicode is a typical double-byte code which can represents all kinds of characters in the world, this dictionary will be applicable for multi-language dictionaries.

Digital libraries have untapped potential for supporting language teaching and learning. This paper describes a new scheme for automating topic-specific language learning using a specially built digital library. Three exercises of different types are generated automatically from the library content: one that learners undertake individually, one in which learners collaborate in pairs, and one in which a group of learners compete. The system aims to foster content-based language learning, which greatly increases students’ motivation, fosters long-term recollection, and can be culturally situated in appropriate ways.

This paper is a follow-up to our ICADL 2006 paper, reporting on our progress over the past year in developing a digital library curriculum. It presents and describes the current curriculum framework, which now includes ten modules and 41 sub-modules. It provides an overview of the curriculum development lifecycle, and our progress through that lifecycle. In particular, it reports on our evaluation of the modules that have been drafted. It concludes with a description of two new technologies – Superimposed Information (SI) to help resource presentation in a module and Visual User model Data Mining (VUDM) to help long-term module upgrade by visualizing the user community and its trends.

In this paper, we describe our ongoing project to help alleviate the digital divide problem among high schools in rural areas of Thailand. The idea is to select, organize, index and distribute useful educational Web contents to schools where the Internet connection is not available. These Web contents can be used by teachers and students to enhance the teaching and learning for many class subjects. We have collaborated with a group of teachers from different high schools in order to gather the requirements for designing our software tools. One of the challenging issues is the variation in computer hardwares and network configuration found in different schools. Some shools have PCs connected to the school’s server via the Local Area Network (LAN). While some other schools have low-performance PCs without any network connection. To support both cases, we provide two solutions via two different search engine tools. These tools support content administrators, e.g., teachers, with the features to organize and index the contents. The tools also provide general users with the features to browse and search for needed information. Since the contents and index are locally stored on hard disk or some removable media such as CD-ROM, the Internet connection is not needed.

This study investigates the optimization of the ordering of retrieved media objects from educational multimedia repositories for a continuously-played presentation such that the total presentation lag through a slow network is minimized. We present a computation-efficient NEH-based heuristic algorithm that can obtain a near-optimal solution with minimal computation time. A simulation experiment shows the average gaps between the idle rateof heuristic solutions and randomly generated sequences are around 26.3%. The results indicate the proposed heuristic solution can significantly reduce the presentation lag as compared to a random ordering approach that is commonly applied in conventional multimedia repositories.

We examine the ‘native’ metadata and organizational structures that individuals create for their personal photo digital libraries, by analyzing the behavior of photo collectors as recorded in 37 autoethnographies and ethnographies. The findings confirm several common assumptions about how people organize their photos that have been the basis for features in earlier photo digital libraries-that photos are commonly organized by time, event, and location, and that collection owners create very little metadata manually. We discuss alternate sources of metadata that arise as a consequence of sharing photos, and consider additional features for photo digital libraries that may be useful in supporting searching and browsing of personal collections.

Despite significant growth of the Web in recent years, some portions of the Web remain largely underdeveloped, as shown in a lack of high quality content and functionality. An example is the Arabic Web, in which a lack of well-structured Web directories has limited users’ ability to browse for Arabic resources. In this research, we proposed an approach to building Web directories for the underdeveloped Web and developed a proof-of-concept prototype called Arabic Medical (AMed) Web Directory that supports browsing of over 5,000 Arabic medical Web sites and pages organized in a hierarchical structure. We conducted an experiment involving Arab subjects and found that AMed directory significantly outperformed a benchmark Arabic Web directory in terms of browsing effectiveness and user ratings. This research thus contributes to developing a useful Web directory for organizing information of the Arabic medical domain and to better understanding of supporting browsing on the underdeveloped Web.

Recently, collaborative tagging has become popular in the web2.0 world. Tags can be helpful if used for the recommendation since they reflect characteristic content features of the resources. However, there are few researches which introduce tags into the recommendation. This paper proposes a tag-based recommendation framework for scientific literatures which models the user interests with tags and literature keywords. A hybrid recommendation algorithm is then applied which is similar to the user-user collaborative filtering algorithm except that the user similarity is measured based on the vector model of user keywords other than the rating matrix, and that the rating is not from the user but represented as user-item similarity computed with the dot-product-based similarity instead of the cosine-based similarity. Experiments show that our tag-based algorithm is better than the baseline algorithm and the extension of user model and dot-product-based similarity computation are also helpful.

Many communities provide Web resource directories to help users find useful resources in the community. A typical example is a resource directory in a homepage of a local government. Crosswalk of the directories of neighboring communities is a crucial function for users to collect useful resources from the communities. However, an appropriate scheme bridging the community directories is required. This paper proposes a few mapping schemes to connect community directories and compares them by applying them to the resource directories of three local governments - Tokyo and Hokkaido in Japan and Chungcheongnam-do in Korea. The mapping schemes use National Diet Library Subject Heading (NDLSH) and/or Nippon Decimal Classification (NDC) as a switching language. Evaluation of the proposed schemes shows their advantages and limitations.

Provides a brief overview of the activities of the IFLA Functional Requirements for Subject Authority Records (FRSAR) working group. Introduces the group’s terms of reference and the work completed so far, including definitions of user tasks and subject entities. Discusses the development of the entity-relationship conceptual model of subject entities in the bibliographic universe.

The partial success in inferring the characteristics of offenders from their criminal behaviour (‘offender profiling’) has relied on limited data and subjective judgments. We therefore sought to determine if Information Retrieval techniques and in particular Language Modelling could be applied directly to existing police digital records of criminal events to identify significant characteristics of offenders. The categories selected were gender and age group. Results showed that distinct differences in characteristics do exist.

Most gazetteers with a global scope contain few local names, and gazetteers with a local scope mostly do not contain foreign names. However, people often use both local and foreign place names in a discourse. We describe some of the challenges in mapping local and global gazetteers that serve different needs and hence may have different structure, granularity and coverage. We pay special attention to the problem of identifying duplicate place descriptions in such registries.

This research aims to develop a model for identifying predictive variables for the selection of the best quality answer in a question-answering (QA) system. It was found that accuracy, completeness and relevance are strong predictors of the quality of the answer.

In this paper a two dimensional two directional pairwise Fisher’s linear discriminant (FLD), (2D

2

pairwise FLD) is proposed which is employed for representation and recognition of Kannada numerals. The proposed methodology is robust as it is an extension of 2D pairwise-FLD[3] which is theoretically more efficient than conventional FLD.

At present, many researches of noun phrase translation are proposed in Natural Language Processing field, but most of them are in dictionary-based with word-by-word translation and similarity selection. The paper proposes a hybrid approach for noun phrase translation, by combining the set theory and grammar’s pattern, and its algorithms, to apply to Vietnamese–English translation. The finding also has good experimental results when applying on Vietnamese noun phrases.

This paper presents a new algorithm called “tree-structured networks” that can automatically construct parent-child (hierarchical structure) and sibling relationships (non-hierarchical structure) among concepts from a set of documents without use of data reduction or standard clustering techniques. The algorithm is applied to bibliographic databases such as INSPEC and EI Compendex toward the objective of enhancing research and development (R&D) management. Deriving tree-structured networks of research topics is an important goal in R&D management study. Parent-child relationships can help identify emerging areas in an existing field of research. Sibling relationships are interesting as well since they could represent interdisciplinary structures among related topical areas. Based on the initial testing on a set of publication abstracts, the proposed algorithm promises to offer richer structural information on relationships in text sources over the standard clustering techniques.

Social tagging systems are a popular means for sharing resources. However, social tagging depends on individual knowledge. We evaluate the effectiveness of tags in describing the resources using support vector machines via classification. We achieved precision and recall at 90.22% and 99.27% respectively, with an average accuracy of 89.84%. Our results show that tags may help users’ group resources into broad categories.

Digital Libraries currently use several advanced information technologies to organize information and make it easy accessible to users. Current digital library trends to be dynamic digital library [1]. It is possible that business rules also can be approached for improving dynamic digital library. Business rules [2] are statements that define or contain some aspects of IT systems by providing a foundation for understanding how an IT system functions. At present, the need for automated business rules is becoming more essential because of the increasing usage of IT systems. However, it is not easy to extract business rules because they are written in a natural language structure and much of it is ignored. Therefore, one important question in this research area is how to automatically extract a business rule from a document? Based on this, information extraction (IE) [3] typically can be applied. Basically, IE is to transform text into information that is more readily analyzed. We believe that if the content of a document is decreased, the accuracy of rules extraction may be increased logically. With this assumption, if irrelevant information is filtered from the document, it is possible to easily extract business rules from the rest. Therefore, this research proposes a method based on probabilistic text classifier to extract synopsis information. It could be said that this work is the pre-processing of a business rules extraction methodology.

We present here the findings of our research to study the “Small World Phenomenon” and the scientific collaboration of authors in the Digital Library domain by using Social Network Analysis metrics. Co-authorship network of prolific authors is created and Social Network Analysis is carried out using UCInet.

In recent years, the world of encyclopedia publishing has been challenged as new collaborative models of online information gathering and sharing have developed. Most notable of these is Wikipedia. Although Wikipedia has a core group of devotees, it has also attracted critical comment and concern, most notably in regard to its quality. In this article we compare the scope of Wikipedia and Encyclopedia Britannica in the subject of biochemistry using a popular first year undergraduate textbook as a benchmark for concepts that should appear in both works, if they are to be considered comprehensive in scope.

This paper identifies the prolific authors at the International Asian Conference on Digital Libraries (ICADL) from 2002 to 2006. To provide a holistic picture, three methods of counting were used, namely whole counting, fractional counting, and first author counting.