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020 _a9783540471288
_9978-3-540-47128-8
024 7 _a10.1007/11899402
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aAdvances in Web Mining and Web Usage Analysis
_h[electronic resource] :
_b6th International Workshop on Knowledge Discovery on the Web, WEBKDD 2004, Seattle, WA, USA, August 22-25, 2004, Revised Selected Papers /
_cedited by Bamshad Mobasher, Olfa Nasraoui, Bing Liu, Brij Masand.
250 _a1st ed. 2006.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2006.
300 _aX, 189 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v3932
505 0 _aWeb Usage Analysis and User Modeling -- Mining Temporally Changing Web Usage Graphs -- Improving the Web Usage Analysis Process: A UML Model of the ETL Process -- Web Personalization and Recommender Systems -- Mission-Based Navigational Behaviour Modeling for Web Recommender Systems -- Complete This Puzzle: A Connectionist Approach to Accurate Web Recommendations Based on a Committee of Predictors -- Collaborative Quality Filtering: Establishing Consensus or Recovering Ground Truth? -- Search Personalization -- Spying Out Accurate User Preferences for Search Engine Adaptation -- Using Hyperlink Features to Personalize Web Search -- Semantic Web Mining -- Discovering Links Between Lexical and Surface Features in Questions and Answers -- Integrating Web Conceptual Modeling and Web Usage Mining -- Boosting for Text Classification with Semantic Features -- Markov Blankets and Meta-heuristics Search: Sentiment Extraction from Unstructured Texts.
520 _aTheWebisaliveenvironmentthatmanagesanddrivesawidespectrumofapp- cations in which a user may interact with a company, a governmental authority, a non-governmental organization or other non-pro?t institution or other users. User preferences and expectations, together with usage patterns, form the basis for personalized, user-friendly and business-optimal services. Key Web business metrics enabled by proper data capture and processing are essential to run an e?ective business or service. Enabling technologies include data mining, sc- able warehousing and preprocessing, sequence discovery, real time processing, document classi?cation, user modeling and quality evaluation models for them. Recipient technologies required for user pro?ling and usage patterns include recommendation systems, Web analytics applications, and application servers, coupled with content management systems and fraud detectors. Furthermore, the inherent and increasing heterogeneity of the Web has - quired Web-based applications to more e?ectively integrate a variety of types of data across multiple channels and from di?erent sources. The development and application of Web mining techniques in the context of Web content, Web usage, and Web structure data has already resulted in dramatic improvements in a variety of Web applications, from search engines, Web agents, and content management systems, to Web analytics and personalization services. A focus on techniques and architectures for more e?ective integration and mining of c- tent, usage,and structure data from di?erent sourcesis likely to leadto the next generation of more useful and more intelligent applications.
650 0 _aArtificial intelligence.
_93407
650 0 _aComputer networks .
_931572
650 0 _aDatabase management.
_93157
650 0 _aInformation storage and retrieval systems.
_922213
650 0 _aApplication software.
_9136476
650 0 _aComputers and civilization.
_921733
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputer Communication Networks.
_9136477
650 2 4 _aDatabase Management.
_93157
650 2 4 _aInformation Storage and Retrieval.
_923927
650 2 4 _aComputer and Information Systems Applications.
_9136478
650 2 4 _aComputers and Society.
_931668
700 1 _aMobasher, Bamshad.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9136479
700 1 _aNasraoui, Olfa.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9136480
700 1 _aLiu, Bing.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9136481
700 1 _aMasand, Brij.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9136482
710 2 _aSpringerLink (Online service)
_9136483
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540471271
776 0 8 _iPrinted edition:
_z9783540831792
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v3932
_9136484
856 4 0 _uhttps://doi.org/10.1007/11899402
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