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Über dieses Buch

This book constitutes the revised selected papers of the combined workshops on Web Information Systems Engineering, WISE 2014, held in Thessaloniki, Greece, in October 2014. The 19 selected papers presented were carefully revised and report from the four workshops: computational social networks, IWCSN 2014, enterprise social networks, Org2 2014, personalization and context-awareness in cloud and service computing, PCS 2014, and data quality and trust in big data, QUAT 2014.



Semi-supervised Learning Algorithm for Binary Relevance Multi-label Classification

The presented paper describes our model for the WISE 2014 challenge multi-label classification task. The goal of the challenge was to implement a multi-label text classification model which maximizes the mean


score on a private test data. The described method involves a binary relevance scheme with linear classifiers trained using stochastic gradient descent. A novel method for determining the values of classifiers’ meta-parameters was developed. In addition, our solution employs the semi-supervised learning which significantly improves the evaluation score. The presented solution won the third place in the challenge. The results are discussed and the supervised and semi-supervised approaches are compared.

Jan Švec

On the Information Diffusion Between Web-Based Social Networks

The topic of Information diffusion has been in the centre of sociology interest for many years. Even before the rise of Online Social Networks (OSNs), social ties and the way the information flows have been studied in traditional real-life social networks. In this paper, we propose the concept of multilayer information flow, by considering every On-line Social Network (OSN) as a separate layer and the information as links connecting these layers. Under such formalization, information is spread from a source layer, while it is diffused in multiple other layers. In order to validate our proposal, experimentations are focused on Reddit and its content, by observing the diffusion of its posts and related content in ImgUr and YouTube.

Giannis Haralabopoulos, Ioannis Anagnostopoulos

Generic Private Social Network for Knowledge Management

The main motivation of this paper is a support of knowledge management for small to medium enterprises (business). We present our tool which was developed to support communication of IT specialists (both from academia and business) using public funding. The main message of this paper is that this tool is quite generic and can be used in different scenarios. Particularly significant is its use as a private social network for knowledge management in a company. Our system is quite rich on actors, knowledge classification schemes, search functionalities, and trust management.

Jiří Kubalík, Jaroslav Pokorný, Martin Vita, Peter Vojtáš

Analysis of Event Logs: Behavioral Graphs

Analysis of event logs is very important discipline used for the evaluation of performance and control-flow issues within the systems. This type of analysis is typically used in process mining sphere, where information systems, for example workflow management systems, enterprise resource planning systems, customer relationship management, supply chain management systems, and business to business systems record transactions and executed activities in a systematic way. Social network analysis takes part of process mining techniques, focused on activity performers, on users. The authors present a new approach to analysis of user behavior in the systems. The approach allows to find behavioral patterns and to find groups of users with similar behavior. An observer can obtain relations between the users on the basis of their similar behavior. The visualization of relations between the users is then presented by so called behavioral graphs. The approach was tested for event log analysis of a virtual company model developed as a multi-agent system by modeling environment MAREA.

Kateřina Slaninová, Dominik Vymětal, Jan Martinovič

Delineating Worker-Centered Organizational Work: Blending BPMS and Social Software Features

Nowadays, companies seek for new technological enablers and adopt new business models to cope with the frenetic pace of change. Such an effort is depicted in the Enterprise 2.0 initiative. Knowledgeable workers should be empowered so that they can help, through their knowledge, the organization they work for to thrive in the today’s highly demanding business environments. Empowerment concerns supporting them to easily gather the knowledge they need as well as to efficiently execute required tasks to accomplish business goals. To provide an efficient working aid, knowledge gathering and task execution should be supported through a unified environment. Towards identifying the features of such a unified environment, we conduct in this paper a two-phase analysis, which leads to the development of a coarse-grained conceptualization of this environment, reflecting a worker-centered organizational work model. This conceptualization is named Worker-Centered Organizational Work Wheel. The Wheel adopts features from both BPMS and social software to enable the integration of knowledge gathering and task execution. Apart from delineating how a knowledgeable worker should work, the Wheel also provides a roadmap showing what features should be offered by any implementation targeting this work model.

Nancy Alexopoulou, Christian Stary, Stefan Oppl

Compliance of the LinkedIn Privacy Policy with the Principles of the ISO 29100:2011 Standard

Sharing personal information in online social networks can be risky, considering that unauthorized users can get access to this information and use it for purposes other than those intended to by the data subjects or those specified by the privacy policy of the online social network. The role of Social Networking Site (SNS) privacy policies is to make clear to the users what information is collected and how it will be used. In this paper we focus on examining whether the current LinkedIn Privacy Policy complies with the privacy principles specified in the ISO 29100:2011 standard. We investigated this conformance by mapping the ISO privacy principles to the privacy policy of the sharing content on LinkedIn, building upon our previous work on Facebook [


]. The results of this examination indicate serious mismatches and can be used for making suggestions that might help the Service Providers to redesign a more privacy respectful LinkedIn.

Alexandra Michota, Sokratis Katsikas

The Use of Social Tagging in Social Business Process Management

Socially driven business process management is the latest paradigm in BPM research. Social elements present in social BPM from one hand and the rigid sequential workflows in traditional BPM systems from another hand had made it difficult to have a full understanding of what social BPM really means, until recently where goal-oriented approach was introduced to overcome this contradiction. One of the main characteristics of social business process management is its inherent collaborative nature during all of its phases starting from the design stage all the way to the execution and improvement phase. This paper aims to provide a model for social BPM in which the post execution tagging of business processes logs is utilised by a process management system to assist future process participants with recommendations for task execution and role assignment. It is believed that this approach will lead to a truly socially driven business process management system where there is transparent and continuous participation of the users.

Mohammad Ehson Rangiha, Bill Karakostas

SocIoS API: A Data Aggregator for Accessing User Generated Content from Online Social Networks

Following the boost in popularity of online social networks, both enterprises and researchers looked for ways to access the social dynamics information and user generated content residing in these spaces. This endeavor, however, presented several challenges caused by the heterogeneity of data and the lack of a common way to access them. The SocIoS framework tries to address these challenges by providing tools that operate on top of multiple popular social networks allowing uniform access to their data. It provides a single access point for aggregating data and functionality from the networks, as well as a set of analytical tools for exploiting them. In this paper we present the SocIoS API, an abstraction layer on top of the social networks exposing operations that encapsulate the functionality of their APIs. Currently, the component provides support for seven social networks and is flexible enough to allow for the seamless addition of more.

Magdalini Kardara, Vasilis Kalogirou, Athanasios Papaoikonomou, Theodora Varvarigou, Konstantinos Tserpes

Integrating Social Media and Open Data in a Cloud-Based Platform for Public Sector Advertising

Nowadays, Public Sector Advertising (PSA) is conveyed as unidirectional top-down stream of messages that clearly separates the content producers (governments usually) from content consumers (citizens). As social networks and Linked Open Government Data (LOGD) initiatives are moving forward e-Government towards connected government, PSA platforms need to embrace the modern paradigms of empowering citizens and communities to increasingly and actively participate in functioning of the society for their own benefits. In this position paper, firstly we present our findings related to the use of content from social networks as public ads and secondly, we propose an open and collaborative platform that supports semantically-enabled, participative PSA.

Daniel Pop, Alejandro Echeverria, Juan Vicente Vidagany

A Survey on Approaches to Modeling Artifact-Centric Business Processes

Business Process Modeling using artifact-centric approach has gained increasing interest over the past few years. The ability to put data and process aspects on an equal footing has made it a powerful tool for efficient business process modeling. The artifact-centric approach is based on key business-relevant entities called business artifacts, which are central for guiding business operations as they navigate through the business operations. The artifact-centric modeling approach can be laid in a four dimensional framework called BALSA for defining business processes, where the four dimensions include business artifacts, lifecycles, services and associations. Based on this data-centric paradigm, several artifact-centric meta-models have been emerged in the recent years. Although all the proposed models claim to support the artifact-centric approach, their support in specifying the BALSA elements of artifacts was not clearly described in the existing literature. This paper reviews all existing approaches to artifact-centric modeling and also discuss to what extent they align with the BALSA framework.

Jyothi Kunchala, Jian Yu, Sira Yongchareon

A Connectivity Based Recommendation Approach for Data Service Mashups

Data service mashup provides a development fashion that integrates heterogeneous data from multiple data sources into a single Web application. This paper focuses on the problem of recommending useful suggestions for developing data service mashups based on the association relationship of data services. Firstly the data service association relationship is analyzed from three angles: the data dependence, inheritance and the potential association between data services. Based on the analysis, a measure of the data service association relationship called connectivity is proposed to assess the relationship of any two data services. Then a recommendation method is proposed to suggest the next useful data services based on the connectivity. The experimental evaluation demonstrates the utility of our method.

Sai Zhang, Guiling Wang, Zhongmei Zhang, Yanbo Han

Using Incentives to Analyze Social Web Services’ Behaviors

This paper discusses how incentives allow social networks to attract more members and reward those that are honest by retaining them. These members referred to as social Web services process users’ requests in return for a certain usage fee and also expose certain behaviors in return of the incentives they receive. The usage fee is linked to a performance level that the social Web service needs to maintain at run time. In the case of any discrepancy between the usage fee and performance level the social Web service is expected to compensate users. However the compensation might not always take place. Simulation results illustrate why honesty is rewarding for social Web services, which has a positive impact on both their performance and the performance of the networks to which they belong.

Zakaria Maamar, Gianpiero Costantino, Marinella Petrocchi, Fabio Martinelli

Creating and Modelling Personal Socio-Economic Networks in On-Line Banking

The banking industry is observing how new competitors threaten its millennial business model by targeting unbanked people, offering new financial services to their customer base, and even enabling new channels for existing services and customers. The knowledge on users, their behaviour, and expectations become a key asset in this new context. Well aware of this situation, the Center for Open Middleware, a joint technology center created by Santander Bank and Universidad Politécnica de Madrid, has launched a set of initiatives to allow the experimental analysis and management of socio-economic information. PosdataP2P service is one of them, which seeks to model the economic ties between the holders of university smart cards, leveraging on the social networks the holders are subscribed to. In this paper we describe the design principles guiding the development of the system, its architecture and some implementation details.

Beatriz San Miguel, Jose M. del Alamo, Juan C. Yelmo

Cloud-Based Video Monitoring Framework: An Approach Based on Software-Defined Networking for Addressing Scalability Problems

Closed-circuit television (CCTV) and Internet protocol (IP) cameras have been applied to a surveillance or monitoring system, from which users can remotely monitor video streams. The system has been employed for many applications such as home surveillance, traffic monitoring, and crime prevention. Currently, cloud computing has been integrated with the video monitoring system for achieving value-added services such as video adjustment, encoding, image/video recognition, and backup services. One of the challenges in this integration is due to the size and geographical scalability problems when video streams are transferred to and retrieved from the cloud services by numerous cameras and users, respectively. Unreliable network connectivity is a major factor that causes the problems. To deal with the scalability problems, this paper proposes a framework designed for a cloud-based video monitoring (CVM) system. In particular, this framework applies two major approaches, namely stream aggregation (SA) and software-defined networking (SDN). The SA approach can reduce the network latency between cameras and cloud services. The SDN approach can achieve the adaptive routing control which improves the network performance. With the SA and SDN approaches applied by the framework, the total latency for transferring video streams can be minimized and the scalability of the CVM system can be significantly enhanced.

Nay Myo Sandar, Sivadon Chaisiri, Sira Yongchareon, Veronica Liesaputra

Context-Awareness in Task Automation Services by Distributed Event Processing

Everybody has to coordinate several tasks everyday, usually in a manual manner. Recently, the concept of Task Automation Services has been introduced to automate and personalize the task coordination problem. Several user centered platforms and applications have arisen in the last years, that let their users configure their very own automations based on third party services. In this paper, we propose a new system architecture for Task Automation Services in a heterogeneous mobile, smart devices, and cloud services environment. Our architecture is based on the novel idea to employ distributed Complex Event Processing to implement innovative mixed execution profiles. The major advantage of the approach is its ability to incorporate context-awareness and real-time coordination in Task Automation Services.

Miguel Coronado, Ralf Bruns, Jürgen Dunkel, Sebastian Stipković

Data Streams Quality Evaluation for the Generation of Alarms in Health Domain

In this paper we present a proposal for managing data streams from sensors that are installed in patients’ homes in order to monitor their health. It focuses on processing the sensors data streams taking into account data quality. In order to achieve this, a data quality model for this kind of data streams and an architecture for the monitoring system are proposed. Besides, our work induces a mechanism for avoiding false alarms generated by data quality problems.

Saúl Fagúndez, Joaquín Fleitas, Adriana Marotta

Multilayer and Multi-agent Data Fusion in WSN

In the wireless sensor networks, the hardware limitations of sensor nodes cause high transmission failure rate. We usually increase the density of nodes to improve the quality of information transmission. However, it is difficult for the limited energy supply, storage, and communication bandwidth to transfer large amount of redundant sensory data. So we use data fusion technology to remove the redundant data as much as possible before the data transmission. Data fusion becomes a research hotspot in recent years. In this paper we propose a multilayer and multi-agent data fusion mode, and analyze the proposed mode performance in three aspects: hops, energy consumption and network delay.The simulation experiments show that, if reasonably suitable parameters, such as the network scale, the number and size of agents, the data processing cost, are selected, the mobile agent mode is much better than the client/server mode.

Sheng Zhang, Xiaodong Liu, Xiaoling Bao, William Wei Song

Strategies for Data Quality Monitoring in Business Processes

The relevance of data quality is continuously increasing in modern enterprises. This is due to the fact that poor data quality has often a negative impact on the business effectiveness and efficiency. Errors, missing or out-of-date data might cause the failure of the business processes and consequently the loss of time and money. In such a scenario, the adoption of tools and methods able to detect and correct process data errors is desirable. In this paper we propose the quality-aware process redesign as a quality improvement method. In particular, the business process is analyzed and modified at design time in order to include Data Quality blocks that are components responsible for the error detection and repair and thus for improving the process reliability. Note that Data Quality blocks can be added to the process workflow using different configurations. This paper aims to describe and compare such configurations. Furthermore, since each configuration impacts in different ways on the process quality and performance, we provide some guidelines for the selection of the configuration able to satisfy the business requirements.

Cinzia Cappiello, Barbara Pernici, Laura Villani

Quality Improvement Framework for Business Oriented Geo-spatial Data

In the past few years, Geo-spatial data quality has received increasing attention and concerns. As more and more business decisions are made based on data analytic result from geo-spatial related data, low quality data means wrong or inappropriate decisions, which could have substantial effects on a business’s future. In this paper, we propose a framework that can systematically ensure and improve geo-spatial data quality throughout the whole life cycle of data.

Xiaofeng Du, William Song


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