Expertise Profiling in Evolving Knowledgecuration Platforms

Expertise modeling has been the subject of extensiveresearch in two main disciplines: Information Retrieval (IR) andSocial Network Analysis (SNA). Both IR and SNA approachesbuild the expertise model through a document-centric approachproviding a macro-perspective on the knowledge emerging fromlarge corpus of static documents. With the emergence of the Webof Data there has been a significant shift from static to evolvingdocuments, through micro-contributions. Thus, the existingmacro-perspective is no longer sufficient to track the evolution ofboth knowledge and expertise. In this paper we present acomprehensive, domain-agnostic model for expertise profiling inthe context of dynamic, living documents and evolving knowledgebases. We showcase its application in the biomedical domain andanalyze its performance using two manually created datasets

The building and application of a semantic platform for an e-research society

This thesis reviews the area of e-Research (the use of electronic infrastructure to support research) and considers how the insight gained from the development of social networking sites in the early 21st century might assist researchers in using this infrastructure. In particular it examines the myExperiment project, a website for e-Research that allows users to upload, share and annotate work flows and associated files, using a social networking framework. This Virtual Organisation (VO) supports many of the attributes required to allow a community of users to come together to build an e-Research society. The main focus of the thesis is how the emerging society that is developing out of my-Experiment could use Semantic Web technologies to provide users with a significantly richer representation of their research and research processes to better support reproducible research. One of the initial major contributions was building an ontology for myExperiment. Through this it became possible to build an API for generating and delivering this richer representation and an interface for querying it. Having this richer representation it has been possible to follow Linked Data principles to link up with other projects that have this type of representation. Doing this has allowed additional data to be provided to the user and has begun to set in context the data produced by myExperiment. The way that the myExperiment project has gone about this task and consideration of how changes may affect existing users, is another major contribution of this thesis. Adding a semantic representation to an emergent e-Research society like myExperiment,has given it the potential to provide additional applications. In particular the capability to support Research Objects, an encapsulation of a scientist's research or research process to support reproducibility. The insight gained by adding a semantic representation to myExperiment, has allowed this thesis to contribute towards the design of the architecture for these Research Objects that use similar Semantic Web technologies. The myExperiment ontology has been designed such that it can be aligned with other ontologies. Scientific Discourse, the collaborative argumentation of different claims and hypotheses, with the support of evidence from experiments, to construct, confirm or disprove theories requires the capability to represent experiments carried out in silico. This thesis discusses how, as part of the HCLS Scientific Discourse subtask group, the myExperiment ontology has begun to be aligned with other scientific discourse ontologies to provide this capability. It also compares this alignment of ontologies with the architecture for Research Objects. This thesis has also examines how myExperiment's Linked Data and that of other projects can be used in the design of novel interfaces. As a theoretical exercise, it considers how this Linked Data might be used to support a Question-Answering system, that would allow users to query myExperiment's data in a more efficient and user-friendly way. It concludes by reviewing all the steps undertaken to provide a semantic platform for an emergent e-Research society to facilitate the sharing of research and its processes to support reproducible research. It assesses their contribution to enhancing the features provided by myExperiment, as well as e-Research as a whole. It considers how the contributions provided by this thesis could be extended to produce additional tools that will allow researchers to make greater use of the rich data that is now available, in a way that enhances their research process rather than significantly changing it or adding extra workload

Review and Alignment of Tag Ontologies for Semantically-Linked Data in Collaborative Tagging Spaces

Abstract—As the number of Web 2.0 sites offering tagging facilities for the users ’ voluntary content annotation increases, so do the efforts to analyze social phenomena resulting from generated tagging and folksonomies. Most of these efforts provide different views for the understanding of various web activities. Results from various experimental research should be utilized to improve existing approaches underlying tagging data and contribute further to weaving the Web. However, in practice, there are not enough solutions taking advantage of these results. Even though we can mine social relations via tagging data, it proves no worth for users if this data cannot be reused. In this paper we propose a solution for tag data representation which allows data reuse across different tagging systems. To achieve this goal, we analyze current social tagging practices, existing folksonomy usage as well as Semantic Web approaches to data annotation and tagging. We survey and compare existing tag ontologies in an attempt to investigate mapping possibilities between different conceptual models. Finally, we present our method for federation among existing ontologies in order to generate re-usable, semantically-linked data that will underly tagging data. I

BlogForever: D3.1 Preservation Strategy Report

This report describes preservation planning approaches and strategies recommended by the BlogForever project as a core component of a weblog repository design. More specifically, we start by discussing why we would want to preserve weblogs in the first place and what it is exactly that we are trying to preserve. We further present a review of past and present work and highlight why current practices in web archiving do not address the needs of weblog preservation adequately. We make three distinctive contributions in this volume: a) we propose transferable practical workflows for applying a combination of established metadata and repository standards in developing a weblog repository, b) we provide an automated approach to identifying significant properties of weblog content that uses the notion of communities and how this affects previous strategies, c) we propose a sustainability plan that draws upon community knowledge through innovative repository design

Analyse temporelle et sémantique des réseaux sociaux typés à partir du contenu de sites généré par des utilisateurs sur le Web

We propose an approach to detect topics, overlapping communities of interest, expertise, trends andactivities in user-generated content sites and in particular in question-answering forums such asStackOverFlow. We first describe QASM (Question & Answer Social Media), a system based on socialnetwork analysis to manage the two main resources in question-answering sites: users and contents. Wealso introduce the QASM vocabulary used to formalize both the level of interest and the expertise ofusers on topics. We then propose an efficient approach to detect communities of interest. It relies onanother method to enrich questions with a more general tag when needed. We compared threedetection methods on a dataset extracted from the popular Q&A site StackOverflow. Our method basedon topic modeling and user membership assignment is shown to be much simpler and faster whilepreserving the quality of the detection. We then propose an additional method to automatically generatea label for a detected topic by analyzing the meaning and links of its bag of words. We conduct a userstudy to compare different algorithms to choose the label. Finally we extend our probabilistic graphicalmodel to jointly model topics, expertise, activities and trends. We performed experiments with realworlddata to confirm the effectiveness of our joint model, studying the users’ behaviors and topicsdynamicsNous proposons une approche pour détecter les sujets, les communautés d'intérêt non disjointes,l'expertise, les tendances et les activités dans des sites où le contenu est généré par les utilisateurs et enparticulier dans des forums de questions-réponses tels que StackOverFlow. Nous décrivons d'abordQASM (Questions & Réponses dans des médias sociaux), un système basé sur l'analyse de réseauxsociaux pour gérer les deux principales ressources d’un site de questions-réponses: les utilisateurs et lecontenu. Nous présentons également le vocabulaire QASM utilisé pour formaliser à la fois le niveaud'intérêt et l'expertise des utilisateurs. Nous proposons ensuite une approche efficace pour détecter lescommunautés d'intérêts. Elle repose sur une autre méthode pour enrichir les questions avec un tag plusgénéral en cas de besoin. Nous comparons trois méthodes de détection sur un jeu de données extrait dusite populaire StackOverflow. Notre méthode basée sur le se révèle être beaucoup plus simple et plusrapide, tout en préservant la qualité de la détection. Nous proposons en complément une méthode pourgénérer automatiquement un label pour un sujet détecté en analysant le sens et les liens de ses mots-clefs.Nous menons alors une étude pour comparer différents algorithmes pour générer ce label. Enfin, nousétendons notre modèle de graphes probabilistes pour modéliser conjointement les sujets, l'expertise, lesactivités et les tendances. Nous le validons sur des données du monde réel pour confirmer l'efficacité denotre modèle intégrant les comportements des utilisateurs et la dynamique des sujet

Linking Folksonomies and Ontologies for Supporting Knowledge Sharing: a State of the Art

Deliverable of ISICIL ANR-funded projectSocial tagging systems have recently become very popular as a means to classify large sets of resources shared among on-line communities over the social Web. However, the folksonomies resulting from the use of these systems revealed limitations: tags are ambiguous and their spelling may vary, and folksonomies are difficult to exploit in order to retrieve or exchange information. This report compares the recent attempts to overcome these limitations and to support the use of folksonomies with formal languages and ontologies from the Semantic Web

Research opportunities for argumentation in social networks

Nowadays, many websites allow social networking between their users in an explicit or implicit way. In this work, we show how argumentation schemes theory can provide a valuable help to formalize and structure on-line discussions and user opinions in decision support and business oriented websites that held social networks between their users. Two real case studies are studied and analysed. Then, guidelines to enhance social decision support and recommendations with argumentation are provided.This work summarises results of the authors joint research, funded by an STMS of the Agreement Technologies COST Action 0801, by the Spanish government grants [CONSOLIDER-INGENIO 2010 CSD2007-00022, and TIN2012-36586-C03-01] and by the GVA project [PROMETEO 2008/051].Heras Barberá, SM.; Atkinson, KM.; Botti Navarro, VJ.; Grasso, F.; Julian Inglada, VJ.; Mcburney, PJ. (2013). Research opportunities for argumentation in social networks. Artificial Intelligence Review. 39(1):39-62. doi:10.1007/s10462-012-9389-0S3962391Amgoud L (2009) Argumentation for decision making. Argumentation in artificial intelligence. Springer, BerlinAnderson P (2007) What is Web 2.0? Ideas, technologies and implications for education. JISC Iechnology and Standards Watch reportBentahar J, Meyer CJJ, Moulin B (2007) Securing agent-oriented systems: an argumentation and reputation-based approach. In: Proceedings of the 4th international conference on information technology: new generations (ITNG 2007), IEEE Computer Society, pp 507–515Buckingham Shum S (2008) Cohere: towards Web 2.0 argumentation. In: Proceedings of the 2nd international conference on computational models of argument, COMMA, pp 28–30Burke R (2002) Hybrid recommender systems: survey and experiments. User Model User-Adapt Interact 12:331–370Cartwright D, Atkinson K (2008) Political engagement through tools for argumentation. In: Proceedings of the second international conference on computational models of argument (COMMA 2008), pp 116–127Chesñevar C, McGinnis J, Modgil S, Rahwan I, Reed C, Simari G, South M, Vreeswijk G, Willmott S (2006) Towards an argument interchange format. Knowl Eng Rev 21(4):293–316Chesñevar CI, Maguitman AG, Gonzàlez MP (2009) Empowering recommendation technologies through argumentation. Argumentation in artificial intelligence. Springer, Berlin, pp 403–422García AJ, Dix J, Simari GR (2009) Argument-based logic programming. Argumentation in artificial intelligence. Springer, BerlinGolbeck J (2006) Generating predictive movie recommendations from trust in social networks. In: Proceedings of the fourth international conference on trust management, LNCS, vol 3986, 93–104Gordon T, Prakken H, Walton D (2007) The Carneades model of argument and burden of proof. Artif Intell 171(10–15):875–896Guha R, Kumar R, Raghavan P, Tomkins A (2004) Propagating trust and distrust. In: Proceedings of the 13th international conference on, World Wide Web, pp 403–412Heras S, Navarro M, Botti V, Julián V (2009) Applying dialogue games to manage recommendation in social networks. In: Proceedings of the 6th international workshop on argumentation in multi-agent aystems, ArgMASHeras S, Atkinson K, Botti V, Grasso F, Julián V, McBurney P (2010a) How argumentation can enhance dialogues in social networks. In: Proceedings of the 3rd international conference on computational models of argument, COMMA, vol 216, pp 267–274Heras S, Atkinson K, Botti V, Grasso F, Julián V, McBurney P (2010b) Applying argumentation to enhance dialogues in social networks. In: ECAI 2010 workshop on computational models of natural argument, CMNA, pp 10–17Karacapilidis N, Tzagarakis M (2007) Web-based collaboration and decision making support: a multi-disciplinary approach. Web-Based Learn Teach Technol 2(4):12–23Kim D, Benbasat I (2003) Trust-related arguments in internet stores: a framework for evaluation. J Electron Commer Res 4(2):49–64Kim D, Benbasat I (2006) The effects of trust-assuring arguments on consumer trust in internet stores: application of Toulmin’s model of argumentation. Inf Syst Rese 17(3):286–300Laera L, Tamma V, Euzenat J, Bench-Capon T, Payne T (2006) Reaching agreement over ontology alignments. In: Proceedings of the 5th international semantic web conference (ISWC 2006)Lange C, Bojãrs U, Groza T, Breslin J, Handschuh S (2008) Expressing argumentative discussions in social media sites. In: Social data on the web (SDoW2008) workshop at the 7th international semantic web conferenceLinden G, Smith B, York J (2003) Amazon.com recommendations: item-to-item collaborative filtering. IEEE Internet Comput 7(1):76–80Linden G, Hong J, Stonebraker M, Guzdial M (2009) Recommendation algorithms, online privacy and more. Commun ACM, 52(5)Mika P (2007) Ontologies are us: a unified model of social networks and semantics. J Web Semant 5(1):5–15Montaner M, López B, de la Rosa JL (2002) Opinion-based filtering through trust. In: Cooperative information agents VI, LNCS, vol 2446, pp 127–144Ontañón S, Plaza E (2008) Argumentation-based information exchange in prediction markets. In: Proceedings of the 5th international workshop on argumentation in multi-agent systems, ArgMASPazzani MJ, Billsus D (2007) Content-based recommendation systems. In: The adaptive web, LNCS, vol 4321, pp 325–341Rahwan I, Zablith F, Reed C (2007) Laying the foundations for a world wide argument web. Artif Intell 171(10–15):897–921Rahwan I, Banihashemi B (2008) Arguments in OWL: a progress report. In: Proceedings of the 2nd international conference on computational models of argument (COMMA), pp 297–310Reed C, Walton D (2007) Argumentation schemes in dialogue. In: Dissensus and the search for common ground, OSSA-07, volume CD-ROM, pp 1–11Sabater J, Sierra C (2002) Reputation and social network analysis in multi-agent systems. In: Proceedings of the 1st international joint conference on autonomous agents and multiagent systems, vol 1, pp 475–482Schafer JB, Konstan JA, Riedl J (2001) E-commerce recommendation applications. Data Min Knowl Discov 5:115–153Schafer JB, Frankowski D, Herlocker J, Sen S (2007) Collaborative filtering recommender systems. In: The adaptive web, LNCS, vol 4321, pp 291–324Schneider J, Groza T, Passant A (2012) A review of argumentation for the aocial semantic web. Semantic web-interoperability, usability, applicability. IOS Press, Washington, DCTempich C, Pinto HS, Sure Y, Staab S (2005) An argumentation ontology for distributed, loosely-controlled and evolvInG Engineering processes of oNTologies (DILIGENT). In: Proceedings of the 2nd European semantic web conference, ESWC, pp 241–256Toulmin SE (1958) The uses of argument. Cambridge University Press, Cambridge, UKTrojahn C, Quaresma P, Vieira R, Isaac A (2009) Comparing argumentation frameworks for composite ontology matching. in: Proceedings of the 6th international workshop on argumentation in multi-agent systems, ArgMASTruthMapping. http://truthmapping.com/Walter FE, Battiston S, Schweitzer F (2007) A model of a trust-based recommendation system on a social network. J Auton Agents Multi-Agent Syst 16(1):57–74Walton D, Krabbe E (1995) Commitment in dialogue: basic concepts of interpersonal reasoning. State University of New York Press, New York, NYWalton D, Reed C, Macagno F (2008) Argumentation schemes. Cambridge University Press, CambridgeWells S, Gourlay C, Reed C (2009) Argument blogging. Computational models of natural argument, CMNAWyner A, Schneider J (2012) Arguing from a point of view. 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Knowledge management and Discovery for advanced Enterprise Knowledge Engineering

2012 - 2013The research work addresses mainly issues related to the adoption of models, methodologies and knowledge management tools that implement a pervasive use of the latest technologies in the area of Semantic Web for the improvement of business processes and Enterprise 2.0 applications. The first phase of the research has focused on the study and analysis of the state of the art and the problems of Knowledge Discovery database, paying more attention to the data mining systems. The most innovative approaches which were investigated for the "Enterprise Knowledge Engineering" are listed below. In detail, the problems analyzed are those relating to architectural aspects and the integration of Legacy Systems (or not). The contribution of research that is intended to give, consists in the identification and definition of a uniform and general model, a "Knowledge Enterprise Model", the original model with respect to the canonical approaches of enterprise architecture (for example with respect to the Object Management - OMG - standard). The introduction of the tools and principles of Enterprise 2.0 in the company have been investigated and, simultaneously, Semantic Enterprise based appropriate solutions have been defined to the problem of fragmentation of information and improvement of the process of knowledge discovery and functional knowledge sharing. All studies and analysis are finalized and validated by defining a methodology and related software tools to support, for the improvement of processes related to the life cycles of best practices across the enterprise. Collaborative tools, knowledge modeling, algorithms, knowledge discovery and extraction are applied synergistically to support these processes. [edited by author]XII n.s

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N