Ackermann / Berendt / Someren Semantics, Web and Mining

Joint International Workshop, EWMF 2005 and KDO 2005, Porto, Portugal, October 3-7, 2005, Revised Selected Papers
2006
ISBN: 978-3-540-47698-6
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 4289, 196 Seiten, eBook

Reihe: Lecture Notes in Computer Science

Finding knowledge – or meaning – in data is the goal of every knowledge d- covery e?ort. Subsequent goals and questions regarding this knowledge di?er amongknowledgediscovery(KD) projectsandapproaches. Onecentralquestion is whether and to what extent the meaning extracted from the data is expressed in a formal way that allows not only humans but also machines to understand and re-use it, i. e. , whether the semantics are formal semantics. Conversely, the input to KD processes di?ers between KD projects and approaches. One central questioniswhetherthebackgroundknowledge,businessunderstanding,etc. that the analyst employs to improve the results of KD is a set of natural-language statements, a theory in a formal language, or somewhere in between. Also, the data that are being mined can be more or less structured and/or accompanied by formal semantics. These questions must be asked in every KD e?ort. Nowhere may they be more pertinent, however, than in KD from Web data (“Web mining”). Thisis due especially to the vast amounts and heterogeneity of data and ba- ground knowledge available for Web mining (content, link structure, and - age), and to the re-use of background knowledge and KD results over the Web as a global knowledge repository and activity space. In addition, the (Sem- tic) Web can serve as a publishing space for the results of knowledge discovery from other resources, especially if the whole process is underpinned by common ontologies.

Zielgruppe

Research

Autoren/Hrsg.

Ackermann, Markus

Berendt, Bettina

Someren, Maarten van

Grobelnik, Marko

Hotho, Andreas

Mladenic, Dunja

Semeraro, Giovanni

Spiliopoulou, Myra

Stumme, Gerd

Svatek, Vojtech

Inhaltsverzeichnis

EWMF Papers.- A Website Mining Model Centered on User Queries.- WordNet-Based Word Sense Disambiguation for Learning User Profiles.- Visibility Analysis on the Web Using Co-visibilities and Semantic Networks.- Link-Local Features for Hypertext Classification.- Information Retrieval in Trust-Enhanced Document Networks.- Semi-automatic Creation and Maintenance of Web Resources with webTopic.- KDO Papers on KDD for Ontology.- Discovering a Term Taxonomy from Term Similarities Using Principal Component Analysis.- Semi-automatic Construction of Topic Ontologies.- Evaluation of Ontology Enhancement Tools.- KDO Papers on Ontology for KDD.- Introducing Semantics in Web Personalization: The Role of Ontologies.- Ontology-Enhanced Association Mining.- Ontology-Based Rummaging Mechanisms for the Interpretation of Web Usage Patterns.