Crestani / Ferragina / Sanderson String Processing and Information Retrieval

13th International Conference, SPIRE 2006, Glasgow, UK, October 11-13, 2006, Proceedings
2006
ISBN: 978-3-540-45775-6
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 4209, 370 Seiten, eBook

Reihe: Lecture Notes in Computer Science

This volume contains the papers presented at the 13th International Symposium on String Processing and Information Retrieval (SPIRE), held October 11-13, 2006, in Glasgow, Scotland. The SPIRE annual symposium provides an opportunity for both new and established researchers to present original contributions to areas such as string processing (dictionary algorithms, text searching, pattern matching, text c- pression, text mining, natural language processing, and automata-based string processing); information retrieval languages, applications, and evaluation (IR modelling, indexing, ranking and ?ltering, interface design, visualization, cro- lingual IR systems, multimedia IR, digital libraries, collaborative retrieval, W- related applications, XML, information retrieval from semi-structured data, text mining, and generation of structured data from text); and interaction of biology and computation (sequencing and applications in molecular biology, evolution and phylogenetics, recognition of genes and regulatory elements, and sequen- driven protein structure prediction). The papers in this volume were selected from 102 papers submitted from over 20 di?erent countries in response to the Call for Papers. A total of 26 submissions were accepted as full papers, yielding an acceptance rate of about 25%. In view of the large number of good-quality submissions the Program Committee decided to accept 5 short papers, that have also been included in the proceedings. SPIRE 2006 also featured two talks by invited speakers: Jamie Callan (Carnegie Mellon University, USA) and Martin Farach-Colton (Rutgers University, USA).

Zielgruppe

Research

Autoren/Hrsg.

Crestani, Fabio

Ferragina, Paolo

Sanderson, Mark

Inhaltsverzeichnis

Web Clustering and Text Categorization.- MP-Boost: A Multiple-Pivot Boosting Algorithm and Its Application to Text Categorization.- TreeBoost.MH: A Boosting Algorithm for Multi-label Hierarchical Text Categorization.- Cluster Generation and Cluster Labelling for Web Snippets: A Fast and Accurate Hierarchical Solution.- Principal Components for Automatic Term Hierarchy Building.- Strings.- Computing the Minimum Approximate ?-Cover of a String.- Sparse Directed Acyclic Word Graphs.- On-Line Repetition Detection.- User Behavior.- Analyzing User Behavior to Rank Desktop Items.- The Intention Behind Web Queries.- Web Search Algorithms.- Compact Features for Detection of Near-Duplicates in Distributed Retrieval.- Inverted Files Versus Suffix Arrays for Locating Patterns in Primary Memory.- Efficient Lazy Algorithms for Minimal-Interval Semantics.- Output-Sensitive Autocompletion Search.- Compression.- A Compressed Self-index Using a Ziv-Lempel Dictionary.- Mapping Words into Codewords on PPM.- Correction.- Improving Usability Through Password-Corrective Hashing.- Word-Based Correction for Retrieval of Arabic OCR Degraded Documents.- Information Retrieval Applications.- A Statistical Model of Query Log Generation.- Using String Comparison in Context for Improved Relevance Feedback in Different Text Media.- A Multiple Criteria Approach for Information Retrieval.- English to Persian Transliteration.- Bio Informatics.- Efficient Algorithms for Pattern Matching with General Gaps and Character Classes.- Matrix Tightness: A Linear-Algebraic Framework for Sorting by Transpositions.- How to Compare Arc-Annotated Sequences: The Alignment Hierarchy.- Web Search Engines.- Structured Index Organizations for High-Throughput Text Querying.- Adaptive Query-Based Sampling of DistributedCollections.- Short Papers.- Dotted Suffix Trees A Structure for Approximate Text Indexing.- Phrase-Based Pattern Matching in Compressed Text.- Discovering Context-Topic Rules in Search Engine Logs.- Incremental Aggregation of Latent Semantics Using a Graph-Based Energy Model.- A New Algorithm for Fast All-Against-All Substring Matching.