TY  - GEN
TY  - GEN
T1  - Semantics, Web and Mining Joint International Workshop, EWMF 2005 and KDO 2005, Porto, Portugal, October 3-7, 2005, Revised Selected Papers
T2  - Lecture Notes in Artificial Intelligence ;
A2  - Ackermann, Markus.
A2  - Ackermann, Markus.
A2  - Berendt, Bettina.
A2  - Berendt, Bettina.
A2  - Grobelnik, Marko.
A2  - Grobelnik, Marko.
A2  - Hotho, Andreas.
A2  - Hotho, Andreas.
A2  - Mladenic, Dunja.
A2  - Mladenic, Dunja.
A2  - Semeraro, Giovanni.
A2  - Semeraro, Giovanni.
A2  - Spiliopoulou, Myra.
A2  - Spiliopoulou, Myra.
A2  - Stumme, Gerd.
A2  - Stumme, Gerd.
A2  - Svatek, Vojtech.
A2  - Svatek, Vojtech.
A2  - Someren, Maarten van.
A2  - Someren, Maarten van.
LA  - English
PP  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg : Imprint: Springer
YR  - 2006
ED  - 1st ed. 2006.
UL  - http://discoverylib.upm.edu.my/discovery/Record/978-3-540-47698-6
AB  - 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.
OP  - 196
CN  - Q334-342
SN  - 9783540476986
KW  - Artificial intelligence.
KW  - Computer communication systems.
KW  - Database management.
KW  - Information storage and retrieval.
KW  - Application software.
KW  - Computers and civilization.
KW  - Artificial Intelligence.
KW  - Computer Communication Networks.
KW  - Database Management.
KW  - Information Storage and Retrieval.
KW  - Information Systems Applications (incl. Internet).
KW  - Computers and Society.
ER  -