TY  - BOOK
AU  - Ackermann,Markus
AU  - Berendt,Bettina
AU  - Grobelnik,Marko
AU  - Hotho,Andreas
AU  - Mladenič,Dunja
AU  - Semeraro,Giovanni
AU  - Spiliopoulou,Myra
AU  - Stumme,Gerd
AU  - Svátek,Vojtěch
AU  - Someren,Maarten
ED  - SpringerLink (Online service)
TI  - Semantics, Web and Mining: Joint International Workshops, EWMF 2005 and KDO 2005, Porto, Portugal, October 3-7, 2005, Revised Selected Papers 
T2  - Lecture Notes in Computer Science,
SN  - 9783540476986
AV  - Q334-342 
U1  - 006.3 23
PY  - 2006///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg
KW  - Computer science
KW  - Computer Communication Networks
KW  - Database management
KW  - Information storage and retrieval systems
KW  - Information systems
KW  - Artificial intelligence
KW  - Computer Science
KW  - Artificial Intelligence (incl. Robotics)
KW  - Database Management
KW  - Information Storage and Retrieval
KW  - Information Systems Applications (incl.Internet)
KW  - Computers and Society
N1  - 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
N2  - 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”). This is 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
UR  - http://dx.doi.org/10.1007/11908678
ER  -