Information Retrieval Technology - primeira edição

EAN (ISBN-13): 9783642171864
ISBN (ISBN-10): 3642171869
Livro de capa dura
Livro de bolso
Ano de publicação: 2010
Editor/Editora: Springer Berlin
627 Páginas
Peso: 0,908 kg
Língua: eng/Englisch

Livro na base de dados desde 2008-06-28T18:49:52+01:00 (Lisbon)
Página de detalhes modificada pela última vez em 2024-03-27T22:01:53+00:00 (Lisbon)
Número ISBN/EAN: 9783642171864

Número ISBN - Ortografia alternativa:
3-642-17186-9, 978-3-642-17186-4
Ortografia alternativa e termos de pesquisa relacionados:
Autor do livro: kan, cheng yen, nakov, jürgen neukirch, lam, preßl
Título do livro: information retrieval, taiwan, information technology, proceedings information, klassenkörpertheorie, internet and web technology, cheng, taipei

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Dados da editora

Autor: Pu-Jen Cheng; Min-Yen Kan; Wai Lam; Preslav Nakov
Título: Lecture Notes in Computer Science; Information Systems and Applications, incl. Internet/Web, and HCI; Information Retrieval Technology - 6th Asia Information Retrieval Societies Conference, AIRS 2010, Taipei, Taiwan, December 1-3, 2010, Proceedings
Editora: Springer; Springer Berlin
627 Páginas
Ano de publicação: 2010-11-16
Berlin; Heidelberg; DE
Língua: Inglês
106,99 € (DE)
109,99 € (AT)
118,00 CHF (CH)
Available
XIII, 627 p. 152 illus.

BC; Hardcover, Softcover / Informatik, EDV/Informatik; Datenbanken; Verstehen; AES; algorithms; calculus; classification; clustering; cross-language IR; digital library; domain-specific IR; e-commerce; entropy; evaluation; exploratory search; folksonomies; machine learning; sentiment analysis; algorithm analysis and problem complexity; data structures; Database Management; Information Storage and Retrieval; Computer and Information Systems Applications; Algorithms; Data Science; Data Storage Representation; Informationsrückgewinnung, Information Retrieval; Data Warehousing; Angewandte Informatik; Algorithmen und Datenstrukturen; EA

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.