000 | 04579nam a22006135i 4500 | ||
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001 | 978-3-540-74951-6 | ||
003 | DE-He213 | ||
005 | 20160624102112.0 | ||
007 | cr nn 008mamaa | ||
008 | 100301s2007 gw | s |||| 0|eng d | ||
020 |
_a9783540749516 _9978-3-540-74951-6 |
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024 | 7 |
_a10.1007/978-3-540-74951-6 _2doi |
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050 | 4 | _aQA76.9.D343 | |
072 | 7 |
_aUNF _2bicssc |
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072 | 7 |
_aUYQE _2bicssc |
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072 | 7 |
_aCOM021030 _2bisacsh |
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082 | 0 | 4 |
_a006.312 _223 |
245 | 1 | 0 |
_aFrom Web to Social Web: Discovering and Deploying User and Content Profiles _h[electronic resource] : _bWorkshop on Web Mining, WebMine 2006, Berlin, Germany, September 18, 2006. Revised Selected and Invited Papers / _cedited by Bettina Berendt, Andreas Hotho, Dunja Mladenic, Giovanni Semeraro. |
260 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2007. |
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264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2007. |
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300 |
_aXI, 164 p. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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490 | 1 |
_aLecture Notes in Computer Science, _x0302-9743 ; _v4737 |
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505 | 0 | _aAn Analysis of Bloggers, Topics and Tags for a Blog Recommender System -- Combining Web Usage Mining and XML Mining in a Real Case Study -- Extracting and Using Attribute-Value Pairs from Product Descriptions on the Web -- Discovering User Profiles from Semantically Indexed Scientific Papers -- Web Usage Mining in Noisy and Ambiguous Environments: Exploring the Role of Concept Hierarchies, Compression, and Robust User Profiles -- From World-Wide-Web Mining to Worldwide Webmining: Understanding People’s Diversity for Effective Knowledge Discovery -- Aspect-Based Tagging for Collaborative Media Organization -- Contextual Recommendation. | |
520 | _aThe World Wide Web is a rich source of information about human behavior. It containslarge amount of data organizedvia interconnected Web pages,traces of information search, user feedback on items of interest, etc. In addition to large data volumes, one of the important characteristics of the Web is its dynamics, where content,structure and usagearechanging over time. This showsup in the rise of related research areas like communities of practice, knowledge mana- ment, Web communities, and peer-to-peer. In particular the notion of colla- rative work and thus the need of its systematic analysis become more and more important. For instance, to develop e?ective Web applications, it is essential to analyze patterns hidden in the usage of Web resources, their contents and their interconnections. Machine learning and data mining methods have been used extensively to ?nd patterns in usage of the network by exploiting both contents and link structures. We have investigated these topics in a series of workshops on Semantic Web Mining (2001, 2002) at the European Conference on Machine Learning / Pr- ciples and Practice of Knowledge Discovery from Databases (ECML/PKDD) conference series, in the selection of papers for the post-proceedings of the - ropean Web Mining Forum 2003 Workshop, published as the Springer LNAI volume 3209 “Web Mining: From Web to Semantic Web” in 2004, as well as in the Knowledge Discovery and Ontologies workshop in 2004 and in the selection ofpapersfor thepost-proceedingsofthe ECML/PKDD2005jointworkshopson Web Mining (European Web Mining Forum) and on Knowledge Discovery and. | ||
650 | 0 | _aComputer science. | |
650 | 0 | _aComputer Communication Networks. | |
650 | 0 | _aDatabase management. | |
650 | 0 | _aData mining. | |
650 | 0 | _aInformation systems. | |
650 | 0 | _aArtificial intelligence. | |
650 | 1 | 4 | _aComputer Science. |
650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
650 | 2 | 4 | _aComputer Communication Networks. |
650 | 2 | 4 | _aDatabase Management. |
650 | 2 | 4 | _aInformation Systems Applications (incl.Internet). |
650 | 2 | 4 | _aComputers and Society. |
700 | 1 |
_aBerendt, Bettina. _eeditor. |
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700 | 1 |
_aHotho, Andreas. _eeditor. |
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700 | 1 |
_aMladenic, Dunja. _eeditor. |
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700 | 1 |
_aSemeraro, Giovanni. _eeditor. |
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710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783540749509 |
786 | _dSpringer | ||
830 | 0 |
_aLecture Notes in Computer Science, _x0302-9743 ; _v4737 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-540-74951-6 |
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_2EBK7817 _cEBK |
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