Information Retrieval Technology: 6th Asia Information Retrieval Societies Conference, AIRS 2010, Taipei, Taiwan, December 1-3, 2010, Proceedings: Lecture Notes in Computer Science, cartea 6458
Editat de Pu-Jen Cheng, Min-Yen Kan, Wai Lam, Preslav Nakoven Limba Engleză Paperback – 16 noi 2010
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Specificații
ISBN-13: 9783642171864
ISBN-10: 3642171869
Pagini: 640
Ilustrații: XIII, 627 p. 152 illus.
Greutate: 0.57 kg
Ediția:2010
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Information Systems and Applications, incl. Internet/Web, and HCI
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3642171869
Pagini: 640
Ilustrații: XIII, 627 p. 152 illus.
Greutate: 0.57 kg
Ediția:2010
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Information Systems and Applications, incl. Internet/Web, and HCI
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
Session 1: IR Models – I.- Relevance Ranking Using Kernels.- Mining YouTube to Discover Extremist Videos, Users and Hidden Communities.- Title-Based Product Search – Exemplified in a Chinese E-commerce Portal.- Relevance Model Revisited: With Multiple Document Representations.- Session 2: Machine Learning for IR – I.- Multi-viewpoint Based Similarity Measure and Optimality Criteria for Document Clustering.- A Text Classifier with Domain Adaptation for Sentiment Classification.- Session 3: User Studies and Evaluation.- Effective Time Ratio: A Measure for Web Search Engines with Document Snippets.- Investigating Characteristics of Non-click Behavior Using Query Logs.- Score Estimation, Incomplete Judgments, and Significance Testing in IR Evaluation.- Poster Session.- Multi-Search: A Meta-search Engine Based on Multiple Ontologies.- Co-HITS-Ranking Based Query-Focused Multi-document Summarization.- Advanced Training Set Construction for Retrieval in Historic Documents.- Ontology-Driven Semantic Digital Library.- Revisiting Rocchio’s Relevance Feedback Algorithm for Probabilistic Models.- When Two Is Better Than One: A Study of Ranking Paradigms and Their Integrations for Subtopic Retrieval.- Connecting Qualitative and Quantitative Analysis of Web Search Process: Analysis Using Search Units.- Transliteration Retrieval Model for Cross Lingual Information Retrieval.- The Role of Lexical Ontology in Expanding the Semantic Textual Content of On-Line News Images.- Order Preserved Cost-Sensitive Listwise Approach in Learning to Rank.- Pseudo-Relevance Feedback Based on mRMR Criteria.- An Integrated Deterministic and Nondeterministic Inference Algorithm for Sequential Labeling.- FolkDiffusion: A Graph-Based Tag Suggestion Method for Folksonomies.- Effectively LeveragingEntropy and Relevance for Summarization.- Machine Learning Approaches for Modeling Spammer Behavior.- Research of Sentiment Block Identification for Customer Reviews Based on Conditional Random Fields.- Semantic Relation Extraction Based on Semi-supervised Learning.- Corpus-Based Arabic Stemming Using N-Grams.- Analysis and Algorithms for Stemming Inversion.- Top-Down and Bottom-Up: A Combined Approach to Slot Filling.- Relation Extraction between Related Concepts by Combining Wikipedia and Web Information for Japanese Language.- A Chinese Sentence Compression Method for Opinion Mining.- Relation Extraction in Vietnamese Text Using Conditional Random Fields.- A Sparse L 2-Regularized Support Vector Machines for Large-Scale Natural Language Learning.- An Empirical Comparative Study of Manual Rule-Based and Statistical Question Classifiers on Heterogeneous Unseen Data.- Constructing Blog Entry Classifiers Using Blog-Level Topic Labels.- Finding Hard Questions by Knowledge Gap Analysis in Question Answer Communities.- Exploring the Visual Annotatability of Query Concepts for Interactive Cross-Language Information Retrieval.- A Diary Study-Based Evaluation Framework for Mobile Information Retrieval.- Dynamics of Genre and Domain Intents.- Query Recommendation Considering Search Performance of Related Queries.- Session 4: NLP for IR – I.- A Local Generative Model for Chinese Word Segmentation.- Re-ranking Summaries Based on Cross-Document Information Extraction.- A Two-Stage Algorithm for Domain Adaptation with Application to Sentiment Transfer Problems.- Domain-Specific Term Rankings Using Topic Models.- Learning Chinese Polarity Lexicons by Integration of Graph Models and Morphological Features.- Session 5: Machine Learning for IR – II.- Learning to Rank withSupplementary Data.- Event Recognition from News Webpages through Latent Ingredients Extraction.- Tuning Machine-Learning Algorithms for Battery-Operated Portable Devices.- Session 6: IR Models – II.- A Unified Iterative Optimization Algorithm for Query Model and Ranking Refinement.- A Study of Document Weight Smoothness in Pseudo Relevance Feedback.- Modeling Variable Dependencies between Characters in Chinese Information Retrieval.- Session 7: Web and QA.- Mining Parallel Documents across Web Sites.- A Revised SimRank Approach for Query Expansion.- Improving Web-Based OOV Translation Mining for Query Translation.- On a Combination of Probabilistic and Boolean IR Models for Question Answering.- Session 8: Multimedia.- Emotion Tag Based Music Retrieval Algorithm.- An Aesthetic-Based Approach to Re-ranking Web Images.
Recenzii
From the reviews:
“The papers presented in these proceedings of the sixth Asia Information Retrieval Conference (AIRS) represent the work by academics and practitioners from across the world. Twenty-six quality papers on a diverse range of topics related to information retrieval technology are divided into eight sections. … This volume is packed with high quality papers and will be most useful for computer and information technology specialists interested in various aspects of information retrieval.” (Madely du Preez, Online Information Review, Vol. 35 (6), 2011)
“The papers presented in these proceedings of the sixth Asia Information Retrieval Conference (AIRS) represent the work by academics and practitioners from across the world. Twenty-six quality papers on a diverse range of topics related to information retrieval technology are divided into eight sections. … This volume is packed with high quality papers and will be most useful for computer and information technology specialists interested in various aspects of information retrieval.” (Madely du Preez, Online Information Review, Vol. 35 (6), 2011)