Advances in Information Retrieval: 29th European Conference on IR Research, ECIR 2007, Rome, Italy, April 2-5, 2007, Proceedings / Edition 1

Table of Contents

Keynote Talks.- The Next Generation Web Search and the Demise of the Classic IR Model.- The Last Half-Century: A Perspective on Experimentation in Information Retrieval.- Learning in Hyperlinked Environments.- Theory and Design.- A Parameterised Search System.- Similarity Measures for Short Segments of Text.- Multinomial Randomness Models for Retrieval with Document Fields.- On Score Distributions and Relevance.- Modeling Term Associations for Ad-Hoc Retrieval Performance Within Language Modeling Framework.- Efficiency.- Static Pruning of Terms in Inverted Files.- Efficient Indexing of Versioned Document Sequences.- Light Syntactically-Based Index Pruning for Information Retrieval.- Sorting Out the Document Identifier Assignment Problem.- Efficient Construction of FM-index Using Overlapping Block Processing for Large Scale Texts.- Peer-to-Peer Networks (In Memory of Henrik Nottelmann).- Performance Comparison of Clustered and Replicated Information Retrieval Systems.- A Study of a Weighting Scheme for Information Retrieval in Hierarchical Peer-to-Peer Networks.- A Decision-Theoretic Model for Decentralised Query Routing in Hierarchical Peer-to-Peer Networks.- Central-Rank-Based Collection Selection in Uncooperative Distributed Information Retrieval.- Result Merging.- Results Merging Algorithm Using Multiple Regression Models.- Segmentation of Search Engine Results for Effective Data-Fusion.- Queries.- Query Hardness Estimation Using Jensen-Shannon Divergence Among Multiple Scoring Functions.- Query Reformulation and Refinement Using NLP-Based Sentence Clustering.- Automatic Morphological Query Expansion Using Analogy-Based Machine Learning.- Advanced Structural Representations for Question Classification and Answer Re-ranking.- Relevance Feedback.- Incorporating Diversity and Density in Active Learning for Relevance Feedback.- Relevance Feedback Using Weight Propagation Compared with Information-Theoretic Query Expansion.- Evaluation.- A Retrieval Evaluation Methodology for Incomplete Relevance Assessments.- Evaluating Query-Independent Object Features for Relevancy Prediction.- Classification and Clustering.- The Utility of Information Extraction in the Classification of Books.- Combined Syntactic and Semantic Kernels for Text Classification.- Fast Large-Scale Spectral Clustering by Sequential Shrinkage Optimization.- A Probabilistic Model for Clustering Text Documents with Multiple Fields.- Filtering.- Personalized Communities in a Distributed Recommender System.- Information Recovery and Discovery in Collaborative Web Search.- Collaborative Filtering Based on Transitive Correlations Between Items.- Entropy-Based Authorship Search in Large Document Collections.- Topic Identification.- Use of Topicality and Information Measures to Improve Document Representation for Story Link Detection.- Ad Hoc Retrieval of Documents with Topical Opinion.- Expert Finding.- Probabilistic Models for Expert Finding.- Using Relevance Feedback in Expert Search.- XML IR.- Using Topic Shifts for Focussed Access to XML Repositories.- Feature- and Query-Based Table of Contents Generation for XML Documents.- Web IR.- Setting Per-field Normalisation Hyper-parameters for the Named-Page Finding Search Task.- Combining Evidence for Relevance Criteria: A Framework and Experiments in Web Retrieval.- Multimedia IR.- Classifier Fusion for SVM-Based Multimedia Semantic Indexing.- Search of Spoken Documents Retrieves Well Recognized Transcripts.- Short Papers.- Natural Language Processing for Usage Based Indexing of Web Resources.- Harnessing Trust in Social Search.- How to Compare Bilingual to Monolingual Cross-Language Information Retrieval.- Multilingual Text Classification Using Ontologies.- Using Visual-Textual Mutual Information and Entropy for Inter-modal Document Indexing.- A Study of Global Inference Algorithms in Multi-document Summarization.- Document Representation Using Global Association Distance Model.- Sentence Level Sentiment Analysis in the Presence of Conjuncts Using Linguistic Analysis.- PageRank: When Order Changes.- Model Tree Learning for Query Term Weighting in Question Answering.- Examining Repetition in User Search Behavior.- Popularity Weighted Ranking for Academic Digital Libraries.- Naming Functions for the Vector Space Model.- Effective Use of Semantic Structure in XML Retrieval.- Searching Documents Based on Relevance and Type.- Investigation of the Effectiveness of Cross-Media Indexing.- Improve Ranking by Using Image Information.- N-Step PageRank for Web Search.- Authorship Attribution Via Combination of Evidence.- Posters.- Cross-Document Entity Tracking.- Enterprise People and Skill Discovery Using Tolerant Retrieval and Visualization.- Experimental Results of the Signal Processing Approach to Distributional Clustering of Terms on Reuters-21578 Collection.- Overall Comparison at the Standard Levels of Recall of Multiple Retrieval Methods with the Friedman Test.- Building a Desktop Search Test-Bed.- Hierarchical Browsing of Video Key Frames.- Active Learning with History-Based Query Selection for Text Categorisation.- Fighting Link Spam with a Two-Stage Ranking Strategy.- Improving Naive Bayes Text Classifier Using Smoothing Methods.- Term Selection and Query Operations for Video Retrieval.- An Effective Threshold-Based Neighbor Selection in Collaborative Filtering.- Combining Multiple Sources of Evidence in XML Multimedia Documents: An Inference Network Incorporating Element Language Models.- Language Model Based Query Classification.- Integration of Text and Audio Features for Genre Classification in Music Information Retrieval.- Retrieval Method for Video Content in Different Format Based on Spatiotemporal Features.- Combination of Document Priors in Web Information Retrieval.- Enhancing Expert Search Through Query Modeling.- A Hierarchical Consensus Architecture for Robust Document Clustering.- Summarisation and Novelty: An Experimental Investigation.- A Layered Approach to Context-Dependent User Modelling.- A Bayesian Approach for Learning Document Type Relevance.

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