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2012 | Buch

Enterprise Information Systems

13th International Conference, ICEIS 2011, Beijing, China, June 8-11, 2011, Revised Selected Papers

herausgegeben von: Runtong Zhang, Juliang Zhang, Zhenji Zhang, Joaquim Filipe, José Cordeiro

Verlag: Springer Berlin Heidelberg

Buchreihe : Lecture Notes in Business Information Processing

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Über dieses Buch

This book contains substantially extended and revised versions of the best papers from the 13th International Conference on Enterprise Information Systems (ICEIS 2011), held in Beijing, China, June 8-11, 2011.

The 27 papers included (plus one invited paper) in this volume were carefully reviewed and selected from 57 full papers presented at the conference (out of 402 submissions). They reflect state-of-the-art research that is often driven by real-world applications, thus successfully relating the academic with the industrial community. The topics covered are: databases and information systems integration, artificial intelligence and decision support systems, information systems analysis and specification, software agents and Internet computing, and human-computer interaction.

Inhaltsverzeichnis

Frontmatter

Invited Paper

Frontmatter
A System-of-Systems Approach to the Analysis and Conservation of Biodiversity
Abstract
Sustainability involves ecological and human aspects whose elements are themselves complex and heterogeneous systems. System-of-Systems (SoS) models provide a unified view of such systems. This paper presents a SoS model of biodiversity and describes its lowest level in detail. The goal is to devise strategies that improve biodiversity for a given region or country subject to certain constraints such as limited budget.
Yannis A. Phillis, Vassilis S. Kouikoglou

Part I: Databases and Information Systems Integration

Frontmatter
Clustering Documents with Maximal Substrings
Abstract
This paper provides experimental results showing that we can use maximal substrings as elementary building blocks of documents in place of the words extracted by a current state-of-the-art supervised word extraction. Maximal substrings are defined as the substrings each giving a smaller number of occurrences even by appending only one character to its head or tail. The main feature of maximal substrings is that they can be extracted quite efficiently in an unsupervised manner. We extract maximal substrings from a document set and represent each document as a bag of maximal substrings. We also obtain a bag of words representation by using a state-of-the-art supervised word extraction over the same document set. We then apply the same document clustering method to both representations and obtain two clustering results for a comparison of their quality. We adopt a Bayesian document clustering based on Dirichlet compound multinomials for avoiding overfitting. Our experiment shows that the clustering quality achieved with maximal substrings is acceptable enough to use them in place of the words extracted by a supervised word extraction.
Tomonari Masada, Atsuhiro Takasu, Yuichiro Shibata, Kiyoshi Oguri
Imbalanced Classification Problems: Systematic Study, Issues and Best Practices
Abstract
This paper provides a systematic study of the issues and possible solutions to the class imbalance problem. A set of standard classification algorithms is considered and their performance on benchmark data is analyzed. Our experiments show that, in an imbalanced problem, the imbalance ratio (IR) can be used in conjunction with the instances per attribute ratio (IAR), to evaluate the appropriate classifier that best fits the situation. Also, MLP and C4.5 are less affected by the imbalance, while SVM generally performs poorly in imbalanced problems. The possible solutions for overcoming these classifier issues are also presented. The overall vision is that when dealing with imbalanced problems, one should consider a wider context, taking into account several factors simultaneously: the imbalance, together with other data-related particularities and the classification algorithms with their associated parameters.
Camelia Lemnaru, Rodica Potolea
Adaptive Information Integration: Bridging the Semantic Gap between Numerical Simulations
Abstract
The increasing complexity and costs of modern production processes makes it necessary to plan processes virtually before they are tested and realized in real environments. Therefore, several tools facilitating the simulation of different production techniques and design domains have been developed. On the one hand there are specialized tools simulating specific production techniques with exactness close to the real object of the simulation. On the other hand there are simulations which simulate whole production processes, but in general do not achieve prediction accuracy comparable to such specialized tools. Hence, the interconnection of tools is the only way, because otherwise the achievable prediction accuracy would be insufficient. In this chapter, a framework is presented that helps to interconnect heterogeneous simulation tools, considering their incompatible file formats, different semantics of data and missing data consistency.
Tobias Meisen, Philipp Meisen, Daniel Schilberg, Sabina Jeschke
PAR-COM: A New Methodology for Post-processing Association Rules
Abstract
The post-processing of association rules is a difficult task, since a huge number of rules that are generated are of no interest to the user. To overcome this problem many approaches have been developed, such as objective measures and clustering. However, objective measures don’t reduce nor organize the collection of rules, therefore making the understanding of the domain difficult. On the other hand, clustering doesn’t reduce the exploration space nor direct the user to find interesting knowledge, therefore making the search for relevant knowledge not so easy. In this context this paper presents the PAR-COM methodology that, by combining clustering and objective measures, reduces the association rule exploration space directing the user to what is potentially interesting. An experimental study demonstrates the potential of PAR-COM to minimize the user’s effort during the post-processing process.
Veronica Oliveira de Carvalho, Fabiano Fernandes dos Santos, Solange Oliveira Rezende, Renan de Padua
Ubiquitous Resource-Aware Clustering of Data Streams
Abstract
With the advance of wireless networks and mobile devices, the concept of ubiquitous data mining was proposed. Because mobile devices are resource-constrained, mining data streams with mobile devices poses a great challenge. Therefore, ubiquitous data stream mining has become one of the newest research topics in data mining. Previous research on ubiquitous data stream clustering mainly adopts the AOG approach. Although the AOG approach can continue with mining under a resource-constrained environment, it sacrifices the accuracy of mining results. In this paper, we propose the RA-HCluster algorithm that can be used in mobile devices for clustering stream data. It adapts algorithm settings and compresses stream data based on currently available resources, so that mobile devices can continue with clustering at acceptable accuracy even under low memory resources. Experimental results show that not only is RA-HCluster more accurate than RA-VFKM, it is able to maintain a low and stable memory usage.
Ching-Ming Chao, Guan-Lin Chao
UF-Evolve: Uncertain Frequent Pattern Mining
Abstract
Many frequent-pattern mining algorithms were designed to handle precise data, such as the FP-tree structure and the FP-growth algorithm. In data mining research, attention has been turned to mining frequent patterns in uncertain data recently. We want frequent-pattern mining algorithms for handling uncertain data. A common way to represent the uncertainty of a data item in record databases is to associate it with an existential probability. In this paper, we propose a novel uncertain-frequent-pattern discover structure, the mUF-tree, for storing summarized and uncertain information about frequent patterns. With the mUF-tree, the UF-Evolve algorithm can utilize the shuffling and merging techniques to generate iterative versions of it. Our main purpose is to discover new uncertain frequent patterns from iterative versions of the mUF-tree. Our preliminary performance study shows that the UF-Evolve algorithm is efficient and scalable for mining additional uncertain frequent patterns with different sizes of uncertain databases.
Shu Wang, Vincent Ng
Formal Fact-Oriented Model Transformations for Cooperative Information Systems Semantic Conceptualisation
Abstract
Information in enterprise is, now more than ever, a fundamental resource. In order to increase enterprise performance, economics paradigms focus on how to better manage it. Information Systems (IS) are systems whose activities are devoted to capture and to store data, to process them and produce knowledge, used by any stakeholders within an enterprise or among different networked enterprises. The modern architecture of information systems is based on distributed networks. An important challenge, to reach higher performance, is to represent and share knowledge managed by those ISs. One of the main issues in making such heterogeneous Cooperative Information Systems (CIS) working together is to remove semantics interoperability barriers. This paper firstly analyses interoperability issues between CISs and then proposes a systematic approach for data models conceptualisation for knowledge explicitation, based on initial conceptual model cleaning rules, expert knowledge injection rules and finally fact-oriented transformation rules. A case study is proposed, related to a work order process in an Enterprise Resource Planning application, Sage X3.
Mario Lezoche, Alexis Aubry, Hervé Panetto
Incorporating Data Concerns into Query Languages for Data Services
Abstract
More and more organizations provide their data on the web via data services – also referred to as Data as a Service (DaaS). Data services combine the strength of database systems and query languages on the one hand with the benefits of service-oriented architecture on the other hand. Data services are increasingly used for data integration. The data provided via data services is often associated with data concerns like privacy, licensing, pricing, quality of data, etc. Hence, data integration tools not only have to mitigate the heterogeneity in data formats and query languages. In addition, also the various data concerns should be preserved when data is published and utilized. Moreover, data service selection and data selection should be based on these data concerns. Current Data Integration systems using data services lack the ability to preserve data concerns while querying multiple services in an integrated environment. In this paper, we design a new querying system which takes data concerns into account. To this end we discuss several models of data concern aware querying and select the best suited one for our system. We describe a querying system where data concern awareness is integrated directly into the XQuery language. We also report on an implementation and experimental evaluation of this system.
Muhammad Intizar Ali, Reinhard Pichler, Hong-Linh Truong, Schahram Dustdar

Part II: Artificial Intelligence and Decision Support Systems

Frontmatter
A Study on Noisy Typing Stream Analysis Using Machine Learning Approach
Abstract
People’s behaviors on using computer keyboard are different. This is particularly the case within disabled community. The differences are reflected by individual’s distinct typing characters such as speed and error patterns, and the environment around. This paper studies features such as keyboard layout, key distance and time gap and provides evidence that these features significantly affect people’s typing performance. A specific user typing behavior, i.e. ‘Hitting Adjacent Key Errors’, is selected from categorized typing behaviors and simulated based on a probabilistic neural network algorithm to correct typing mistakes. Results demonstrate a high performance of the designed model, about 70% of all tests score above Basic Correction Rate, and simulation also shows a very unstable trend of user’s ‘Hitting Adjacent Key Errors’ behavior with specific datasets used by the research. Further work is suggested in the conclusion.
Jun Li
Intelligent Information Acquisition and Utilization in Safety Evaluation Decision Making Process of Power Generation Enterprises
Abstract
Modern information technologies are playing an increasing importantly role in safety production assessment of thermal power plants (TPPs). This paper investigates historical knowledge acquisition and utilization issue in safety evaluation of power generation enterprise and provides a case-based approach for the safety assessment decision making of TPPs (MSSATPP). A case matching method named CBR-Grey which ingrates Delphi approach and Grey System theory is proposed. Based on this method, we implement a prototype of information acquisition and utilization system (CBRSYS-TPP) for MSSATPP. We use this system to complete two distinct comparative experiments and validate the effectiveness and excellent comprehensive performance of CBR-Grey. CBRSYS-TPP is hopeful to be a powerful decision tool for panel of experts during their evaluation.
Dongxiao Gu, Changyong Liang, Jinhong Zhong, Jun Wang, Wenxing Lu, Junyuan Song, Wenwen Lv, Yifeng Wu
Outperforming Mutation Operator with Random Building Block Operator in Genetic Algorithms
Abstract
The refinement process in genetic algorithms is carried out mainly by crossover and mutation operators. In their classical forms these operators need to be tuned through parameters and they are not efficient enough. Moreover, lack of sufficient variation in the population causes genetic algorithms to stagnate at local optima. In this work a new dynamic mutation operator called random building block operator with variable mutation rate proportionate to the number of variables in the problem is proposed. This operator does not require any pre-fixed parameter. At runtime it dynamically takes into account the length of the binary presentation of the individual and the number of variables in the problem and replaces a randomly selected section of the individual by a randomly generated bit string of the same size. Experimentation with 33 test functions, 231 test cases and 11550 test runs proved the superiority of the proposed dynamic mutation operator over single-point mutation operator with 1%, 5% and 8% mutation rates and the multipoint mutation operator with 5%, 8% and 15% mutation rates. Based on the experimentation results the random building block operator can be proposed as a better substitution of single-point and multipoint mutation operators.
Ghodrat Moghadampour
Automating Texas Hold’em Poker with PLICAS
Abstract
Influenced by the possibilities of the Internet poker has become a popular online game. Spurred by this development, automated poker got into the focus of research in game theory (GT), artificial intelligence (AI) and multi-agent systems (MAS). This paper describes the development and evaluation of PLICAS, a poker bot designed for the ‘Texas Hold’em Fixed Limit Heads-up’ variant. The poker bot integrates approaches, such as opponent modeling, abstraction techniques, and case-based reasoning. PLICAS also introduces simulation-based methods for the exploitation of the opponent’s play. Participation in the 2010 AAAI Computer Poker Competition (ACPC) shows that PLICAS has a lot of potential but suffers from a vulnerable opponent modeling strategy.
Michael Schwind, Christian Friedrich
An Event-Based Service Framework for Learning, Querying and Monitoring Multivariate Time Series
Abstract
We propose an event-based service framework for Multivariate Time Series Analytics (MTSA) that supports model definition, querying, parameter learning, model evaluation, monitoring, and decision recommendation on events. Our approach combines the strengths of both domain-knowledge-based and formal-learning-based approaches for maximizing utility on events over multivariate time series. More specifically, we identify multivariate time series parametric estimation problems, in which the objective function is dependent on the time points from which the parameters are learned. We propose an algorithm that guarantees to find the optimal time point(s), and we show that our approach produces results that are superior to those of the domain-knowledge-based approach and the logit regression model. We also develop MTSA data model and query language for the services of parameter learning, querying, and monitoring.
Chun-Kit Ngan, Alexander Brodsky, Jessica Lin
From Natural Language Software Specifications to UML Class Models
Abstract
Software specifications are typically captured in natural languages and then software analysts manually analyzed and produce the software models such class models. Various approaches, frameworks and tool have been presented for automatic translation of software models such as CM-Builder, Re-Builder, NL-OOML, GOOAL, etc. However, the experiments with these tools show that they do not provide with high accuracy in translation. Major reason of less accuracy reported in the literature is the ambiguous and informal nature of the natural languages. In this article, we aim to address this issue and present a better approach for processing natural languages and produce more accurate UML software models. The presented approach is based on Semantic Business Vocabulary and Rules (SBVR) recently adopted standard by OMG. Our approach works as the natural language software specifications are first mapped to SBVR rules representation. SBVR rules are easy to translate other formal representations such as OCL and UML as SBVR is based on higher order logic. A case study solved with our tool NL2UMLviaSBVR is also presented and the a comparative analysis of our tools research with other available tools show that use of SBVR in NL to UML translation helps to improve the accuracy.
Imran Sarwar Bajwa, M. Abbas Choudhary

Part III: Information Systems Analysis and Specification

Frontmatter
On the Use of Software Visualization to Analyze Software Evolution: An Interactive Differential Approach
Abstract
Software evolution is one of the most important topics in modern software engineering research. This activity requires the analysis of large amounts of data describing the current software system structure as well as its previous history. Software visualization can be helpful in this scenario, as it can summarize this complex data into easy to interpret visual scenarios. This paper presents an interactive differential approach for visualizing software evolution. The approach builds multi-view structural descriptions of a software system directly from its source code, and uses colors to differentiate it from any other previous version. This differential approach is highly interactive allowing the user to quickly brush over many pairs of versions of the system. As a proof of concept, we used the approach to analyze eight versions of an open source system and found out it was useful to quickly identify hot spot and code smell candidates in them.
Renato Lima Novais, Glauco de F. Carneiro, Paulo R. M. Simões Júnior, Manoel Gomes Mendonça
Temporal Management of WS-BPEL Processes
Abstract
WS-BPEL is de-facto industry standard for business processes. One of its major shortcomings is lack of temporal management capabilities. WS-BPEL offers no possibility for definition, calculation and monitoring of temporal values such as activity duration and deadlines as well as checking the temporal conformance of processes. This paper tackles temporal management of WS-BPEL based on two different techniques: interval-based and probabilistic. This paper describes temporal management of cooperating WS-BPEL abstract and executable processes. We have implemented a temporal management prototype as a WS-BPEL extension.
Amirreza Tahamtan, Christian Os̈terle, A. Min Tjoa, Abdelkader Hameurlain
Model Based Testing in Software Product Lines
Abstract
This article describes an approach for test case generation in Software Product Lines, using Model Driven. Our proposal defines a set of metamodels, models and algorithms, all of them organized and managed in a 5-step process, which are implemented in a tool specifically developed for this goal, Pralíntool.
Pedro Reales, Macario Polo, Danilo Caivano
A Set of Well-Formedness Rules to Checking the Consistency of the Software Processes Based on SPEM 2.0
Abstract
Considering the need to avoid errors in a software process, this paper proposes checking it before enactment. Process checking is the activity of verifying the correctness and the consistency of a process. In this paper, process checking is made from a set of well-formedness rules specified from the SPEM 2.0 metamodel. The well-formedness rules are described using the Unified Modeling Language - UML multiplicity and First-Order Predicate Logic – FOLP and their use and evaluation are made using a part of the OpenUP process.
Eliana B. Pereira, Ricardo M. Bastos, Toacy C. Oliveira, Michael C. Móra
A Multiobjective Optimization Approach to the Software Release Planning with Undefined Number of Releases and Interdependent Requirements
Abstract
In software development, release planning is a complex activity which involves several aspects related to which requirements are going to be developed in each release of the system. The planning must meet the customers’ needs and comply with existing constraints. This paper presents an approach based on multiobjective optimization for release planning. The approach tackles formulations when the number of releases is not known a priori and also when the stakeholders have a desired number of releases (target). The optimization model is based on stakeholders’ satisfaction, business value and risk management. Requirements interdependencies are also considered. In order to validate the approach, experiments are carried out and the results indicates the validity of the proposed approach.
Marcia Maria Albuquerque Brasil, Thiago Gomes Nepomuceno da Silva, Fabricio Gomes de Freitas, Jerffeson Teixeira de Souza, Mariela Inés Cortés
Cost Estimation of Web Applications through Knowledge Elicitation
Abstract
Objective – The objective of this paper is detail the use of tacit knowledge elicited from domain experts in the domain of Web effort estimation to build an expert-based Web effort model for a medium-size Web company In Auckland (New Zealand). Method – A single-company Web effort estimation model was built using Bayesian Networks (BN), using knowledge solely elicited from two domain experts who were experienced Web project managers. The model was validated using data from eleven past finished Web projects. Results – The BN model has to date been successfully used to estimate effort for numerous Web projects developed by this Company. Conclusions – Our results suggest that, at least for the Web Company that participated in the case study, the use of models that allow the representation of uncertainty, inherent in effort estimation, can outperform expert-based estimates. Thus far, another nine companies in New Zealand, and on in Brazil have also benefited from using Bayesian Networks, with very promising results.
Emilia Mendes

Part IV: Software Agents and Internet Computing

Frontmatter
Applying Conflict Management Process to Wiki Communities
Abstract
Conflicts are disagreements among members and imply incompatible goals, whishes and interests. Unhandled conflicts can negatively impact group performance and members’ satisfaction. In virtual communities, members discuss when performing collaboratively online tasks so that conflicts can arise. Wiki communities are popular virtual communities that involve an expressive number of members for the online production of articles. Conflicts in wiki context are then critical, being responsible for damaging articles’ quality and even wiki credibility. We propose a management process that includes activities for identification, analysis, response, and monitoring and control of conflicts for wiki communities. In order to explain the activities and evaluate the process, we use Wikipedia.
Juliana de Melo Bezerra, Celso Massaki Hirata
Research on Grid-Based Mobile Business Process and Analysis on Process Simulation
Abstract
Since the emergence of mobile commerce, there have been much research and practice on how to improve wireless communication technology and safety technology, however, the research which integrated wireless technology and business processes of the original e-commerce is still in its early stage, lacking of systematic analysis and theoretical support regarding the information sharing, business collaboration, and effectively access of mobile devices in practice. In this paper, mobile business processes is the research object. On the basis of combing and analyzing the current mobile business process, utilizing the grid management theory construct mobile business process based on grid. Furthermore, a quantitative simulation will be made on non-grid and grid-based mobile business processes in order to prove the superiority of mobile business processes based on grid.
Dan Chang, Li Si

Part V: Human-Computer Interaction

Frontmatter
Understanding User’s Acceptance of Social Shopping Websites: Effects of Social Comparison and Trust
Abstract
Social shopping websites are among the latest developments in E-commerce to combine the power of social networking with Internet shopping to provide a unique online experience. While the adoption of information technology is well studied, new theoretical development is needed to account for the specific characteristics of social shopping websites. This study augments the TAM (Technology Acceptance Model) with social factors including an online shopper’s tendency to social comparison, and trust in information privacy and data security. Results provide significant support of the extended model. Directions for future research are discussed.
Jia Shen
Seeing Social Software Analysis and Evaluation through the Lenses of Culture
Abstract
Social software is a growing reality worldwide, while the analysis and evaluation of this kind of system still is a quite unexplored challenge. The complex scenario of social software has been marked by the diversity of users, their limitations, preferences, cultural aspects such as values, beliefs, customs and so on. This paper sheds light on this scenario proposing a culturally aware artifact to support designers in the task of analyzing and evaluating social software, taking values and other cultural issues into account in an explicit way. The artifact, named VF4SS, was used by a group of designers to evaluate five different prototypes of systems for supporting cross-cultural collaboration. The results obtained from this activity demonstrate that the artifact can bring effective contributions to the evaluation as well as to the design of social software.
Roberto Pereira, M. Cecília C. Baranauskas
Electronic Government in Brazil: Evaluating Brazilian Initiative and How to Improve It
Abstract
This article presents an overview of a major e-government site in Brazil, the Transparency Portal, and makes a comparison with electronic government of some other countries, in order to assess the degree of accessibility of each site. To obtain the results, the validation tools ASES, DaSilva and TotalValidator have been used to evaluate the sites based on e-MAG and WCAG. A survey with entities, such as NGOs and ordinary users is also presented, aiming at evaluating the Transparency Portal according to criteria such as navigation and ease of use. These assessments and a proposed architecture will be used as suggestions for improving the Brazilian site and make it easier to use and accessible to a greater number of citizens, regardless of educational level and specific needs.
Giovanni Bogéa Viana, Maria Beatriz Felgar de Toledo

Part VI: Enterprise Architecture

Frontmatter
A Service-Oriented Framework for Distributed Collaborative Knowledge Work
Abstract
Business data of a company, latest research results of an university or learning content in education – these are just some of many possible examples to illustrate that knowledge is the key factor in modern society. However, the information flood and the growing complexity of data made it more difficult to manage relevant data and distinguish between irrelevant information. Furthermore, there is now a challenge not only store data in an information system but also to remove them if desired. In this article WasabiBeans, a service-oriented framework for distributed collaborative knowledge work, is presented. WasabiBeans provides virtual knowledge spaces that are self-administrated by the users. This article outlines the framework’s powerful authentication and authorization infrastructure as well as a flexible user-driven repository integration – WasabiPipes – to build up complex knowledge networks.
Jonas Schulte
IS/IT Resources and Business Value: Operationalization of an Information Oriented Framework
Abstract
Several studies have highlighted the importance of information and information quality in organisations and thus information is regarded as key determinant for the success and organisational performance. In this paper, we review selected contributions and introduce a model that shows how IS/IT resources and capabilities could be interlinked with IS/IT utilization, organizational performance and business value. Complementing other models and frameworks, we explicitly consider information from a management maturity, quality and risk perspective and show how the new framework can be operationalized with existing assessment approaches by using empirical data from four industrial case studies.
Alexander Borek, Markus Helfert, Mouzhi Ge, Ajith Kumar Parlikad
Backmatter
Metadaten
Titel
Enterprise Information Systems
herausgegeben von
Runtong Zhang
Juliang Zhang
Zhenji Zhang
Joaquim Filipe
José Cordeiro
Copyright-Jahr
2012
Verlag
Springer Berlin Heidelberg
Electronic ISBN
978-3-642-29958-2
Print ISBN
978-3-642-29957-5
DOI
https://doi.org/10.1007/978-3-642-29958-2