Content-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.
Author(s): Saadia Malik, Gabriella Kazai, Mounia Lalmas (auth.), Norbert Fuhr, Mounia Lalmas, Saadia Malik, Gabriella Kazai (eds.)
Series: Lecture Notes in Computer Science 3977 : Information Systems and Applications, incl. Internet/Web, and HCI
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2006
Language: English
Pages: 556
Tags: Information Storage and Retrieval; Information Systems Applications (incl.Internet); Database Management
Front Matter....Pages -
Overview of INEX 2005....Pages 1-15
INEX 2005 Evaluation Measures....Pages 16-29
EPRUM Metrics and INEX 2005....Pages 30-42
HiXEval: Highlighting XML Retrieval Evaluation....Pages 43-57
The Interpretation of CAS....Pages 58-71
TIJAH Scratches INEX 2005: Vague Element Selection, Image Search, Overlap, and Relevance Feedback....Pages 72-87
XFIRM at INEX 2005: Ad-Hoc and Relevance Feedback Tracks....Pages 88-103
The Effect of Structured Queries and Selective Indexing on XML Retrieval....Pages 104-118
Searching XML Documents – Preliminary Work....Pages 119-133
Query Evaluation with Structural Indices....Pages 134-145
B 3 -SDR and Effective Use of Structural Hints....Pages 146-160
Field-Weighted XML Retrieval Based on BM25....Pages 161-171
XML Retrieval Based on Direct Contribution of Query Components....Pages 172-186
Using the INEX Environment as a Test Bed for Various User Models for XML Retrieval....Pages 187-195
The University of Kaiserslautern at INEX 2005....Pages 196-210
Parameter Estimation for a Simple Hierarchical Generative Model for XML Retrieval....Pages 211-224
Probabilistic Retrieval, Component Fusion and Blind Feedback for XML Retrieval....Pages 225-239
GPX – Gardens Point XML IR at INEX 2005....Pages 240-253
Implementation of a High-Speed and High-Precision XML Information Retrieval System on Relational Databases....Pages 254-267
The Dynamic Retrieval of XML Elements....Pages 268-281
TopX and XXL at INEX 2005....Pages 282-295
When a Few Highly Relevant Answers Are Enough....Pages 296-305
RMIT University at INEX 2005: Ad Hoc Track....Pages 306-320
SIRIUS: A Lightweight XML Indexing and Approximate Search System at INEX 2005....Pages 321-335
Machine Learning Ranking and INEX’05....Pages 336-343
Relevance Feedback for Structural Query Expansion....Pages 344-357
NLPX at INEX 2005....Pages 358-372
From Natural Language to NEXI, an Interface for INEX 2005 Queries....Pages 373-387
Processing Heterogeneous Collections in XML Information Retrieval....Pages 388-397
The Interactive Track at INEX 2005....Pages 398-410
What Do Users Think of an XML Element Retrieval System?....Pages 411-421
Users Interaction with the Hierarchically Structured Presentation in XML Document Retrieval....Pages 422-431
XML Documents Clustering by Structures....Pages 432-442
A Flexible Structured-Based Representation for XML Document Mining....Pages 443-457
Sequential Pattern Mining for Structure-Based XML Document Classification....Pages 458-468
Transforming XML Trees for Efficient Classification and Clustering....Pages 469-480
Clustering XML Documents Using Self-organizing Maps for Structures....Pages 481-496
INEX 2005 Multimedia Track....Pages 497-510
Integrating Text Retrieval and Image Retrieval in XML Document Searching....Pages 511-524
Combining Image and Structured Text Retrieval....Pages 525-539
Multimedia Strategies for B 3 -SDR, Based on Principal Component Analysis....Pages 540-553
Back Matter....Pages -
