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020 _a9783540349631
_9978-3-540-34963-1
024 7 _a10.1007/11766278
_2doi
050 4 _aQA76.9.D35
050 4 _aQ350-390
072 7 _aUMB
_2bicssc
072 7 _aGPF
_2bicssc
072 7 _aCOM021000
_2bisacsh
072 7 _aUMB
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072 7 _aGPF
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082 0 4 _a005.73
_223
082 0 4 _a003.54
_223
245 1 0 _aAdvances in XML Information Retrieval and Evaluation
_h[electronic resource] :
_b4th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2005, Dagstuhl Castle, Germany, November 28-30, 2005. Revised and Selected Papers /
_cedited by Norbert Fuhr, Mounia Lalmas, Saadia Malik, Gabriella Kazai.
250 _a1st ed. 2006.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2006.
300 _aXII, 556 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aInformation Systems and Applications, incl. Internet/Web, and HCI,
_x2946-1642 ;
_v3977
505 0 _aOverview of INEX 2005 -- INEX 2005 Evaluation Measures -- EPRUM Metrics and INEX 2005 -- HiXEval: Highlighting XML Retrieval Evaluation -- The Interpretation of CAS -- TIJAH Scratches INEX 2005: Vague Element Selection, Image Search, Overlap, and Relevance Feedback -- XFIRM at INEX 2005: Ad-Hoc and Relevance Feedback Tracks -- The Effect of Structured Queries and Selective Indexing on XML Retrieval -- Searching XML Documents – Preliminary Work -- Query Evaluation with Structural Indices -- B 3-SDR and Effective Use of Structural Hints -- Field-Weighted XML Retrieval Based on BM25 -- XML Retrieval Based on Direct Contribution of Query Components -- Using the INEX Environment as a Test Bed for Various User Models for XML Retrieval -- The University of Kaiserslautern at INEX 2005 -- Parameter Estimation for a Simple Hierarchical Generative Model for XML Retrieval -- Probabilistic Retrieval, Component Fusion and Blind Feedback for XML Retrieval -- GPX – Gardens Point XML IR at INEX 2005 -- Implementation of a High-Speed and High-Precision XML Information Retrieval System on Relational Databases -- The Dynamic Retrieval of XML Elements -- TopX and XXL at INEX 2005 -- When a Few Highly Relevant Answers Are Enough -- RMIT University at INEX 2005: Ad Hoc Track -- SIRIUS: A Lightweight XML Indexing and Approximate Search System at INEX 2005 -- Machine Learning Ranking and INEX’05 -- Relevance Feedback for Structural Query Expansion -- NLPX at INEX 2005 -- From Natural Language to NEXI, an Interface for INEX 2005 Queries -- Processing Heterogeneous Collections in XML Information Retrieval -- The Interactive Track at INEX 2005 -- What Do Users Think of an XML Element Retrieval System? -- Users Interaction with the Hierarchically Structured Presentation in XML Document Retrieval -- XML Documents Clusteringby Structures -- A Flexible Structured-Based Representation for XML Document Mining -- Sequential Pattern Mining for Structure-Based XML Document Classification -- Transforming XML Trees for Efficient Classification and Clustering -- Clustering XML Documents Using Self-organizing Maps for Structures -- INEX 2005 Multimedia Track -- Integrating Text Retrieval and Image Retrieval in XML Document Searching -- Combining Image and Structured Text Retrieval -- Multimedia Strategies for B 3-SDR, Based on Principal Component Analysis.
520 _aContent-oriented XML retrieval has been receiving increasing interest due to the widespread use of eXtensible Markup Language (XML), which is becoming a standard document format on the Web, in digital libraries,and publishing. By exploiting the enriched source of syntactic and semantic information that XML markup provides, XML information retrieval (IR) systems aim to implement a more focused retrieval strategy and return document components, so-called XML elements – instead of complete documents – in response to a user query. This focused retrieval approach is of particular bene?t for collections containing long documents or documents covering a wide variety of topics (e.g., books, user manuals, legal documents, etc.), where users’ e?ort to locate relevant content can be reduced by directing them to the most relevant parts of the documents. Implementing this, more focused, retrieval paradigm means that an XML IR system needs not only to ?nd relevant information in the XML documents, but it also has to determine the appropriate level of granularity to be returned to the user. In addition, the relevance of a retrieved component may be dependent on meeting both content and structural query conditions.
650 0 _aData structures (Computer science).
650 0 _aInformation theory.
650 0 _aInformation storage and retrieval systems.
650 0 _aApplication software.
650 0 _aDatabase management.
650 1 4 _aData Structures and Information Theory.
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aComputer and Information Systems Applications.
650 2 4 _aDatabase Management.
700 1 _aFuhr, Norbert.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aLalmas, Mounia.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aMalik, Saadia.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aKazai, Gabriella.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540349624
776 0 8 _iPrinted edition:
_z9783540825357
830 0 _aInformation Systems and Applications, incl. Internet/Web, and HCI,
_x2946-1642 ;
_v3977
856 4 0 _uhttps://doi.org/10.1007/11766278
912 _aZDB-2-SCS
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