Advances in Information Retrieval Theory Second International Conference on the Theory of Information Retrieval, ICTIR 2009 Cambridge, UK, September 10-12, 2009 Proceedings /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Azzopardi, Leif (Επιμελητής έκδοσης), Kazai, Gabriella (Επιμελητής έκδοσης), Robertson, Stephen (Επιμελητής έκδοσης), Rüger, Stefan (Επιμελητής έκδοσης), Shokouhi, Milad (Επιμελητής έκδοσης), Song, Dawei (Επιμελητής έκδοσης), Yilmaz, Emine (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2009.
• Σειρά: Lecture Notes in Computer Science, 5766
• Θέματα: Computer science.; Algorithms.; Database management.; Data mining.; Information storage and retrieval.; Artificial intelligence.; Computer Science.; Information Storage and Retrieval.; Artificial Intelligence (incl. Robotics).; Data Mining and Knowledge Discovery.; Database Management.; Algorithm Analysis and Problem Complexity.; Information Systems Applications (incl. Internet).

 This book constitutes the refereed proceedings of the Second International Conference on the Theory of Information Retrieval, ICTIR 2009, held in Cambridge, UK, in September 2009. The 18 revised full papers, 14 short papers, and 11 posters presented together with one invited talk were carefully reviewed and selected from 82 submissions. The papers are categorized into four main themes: novel IR models, evaluation, efficiency, and new perspectives in IR. Twenty-one papers fall into the general theme of novel IR models, ranging from various retrieval models, query and term selection models, Web IR models, developments in novelty and diversity, to the modeling of user aspects. There are four papers on new evaluation methodologies, e.g., modeling score distributions, evaluation over sessions, and an axiomatic framework for XML retrieval evaluation. Three papers focus on the issue of efficiency and offer solutions to improve the tractability of PageRank, data cleansing practices for training classifiers, and approximate search for distributed IR. Finally, four papers look into new perspectives of IR and shed light on some new emerging areas of interest, such as the application and adoption of quantum theory in IR. 

 Invited Talk -- Is There Something Quantum-Like about the Human Mental Lexicon? -- Regular Papers -- Probably Approximately Correct Search -- PageRank: Splitting Homogeneous Singular Linear Systems of Index One -- Training Data Cleaning for Text Classification -- Semi-parametric and Non-parametric Term Weighting for Information Retrieval -- Bridging Language Modeling and Divergence from Randomness Models: A Log-Logistic Model for IR -- Ordinal Regression Based Model for Personalized Information Retrieval -- Navigating in the Dark: Modeling Uncertainty in Ad Hoc Retrieval Using Multiple Relevance Models -- A Belief Model of Query Difficulty That Uses Subjective Logic -- “A term is known by the company it keeps”: On Selecting a Good Expansion Set in Pseudo-Relevance Feedback -- An Effective Approach to Verbose Queries Using a Limited Dependencies Language Model -- Time-Sensitive Language Modelling for Online Term Recurrence Prediction -- Score Distributions in Information Retrieval -- Modeling the Score Distributions of Relevant and Non-relevant Documents -- Modeling Expected Utility of Multi-session Information Distillation -- Specificity Aboutness in XML Retrieval -- An Effectiveness Measure for Ambiguous and Underspecified Queries -- An Analysis of NP-Completeness in Novelty and Diversity Ranking -- From “Identical” to “Similar”: Fusing Retrieved Lists Based on Inter-document Similarities -- Short Papers -- A Quantum-Based Model for Interactive Information Retrieval -- The Quantum Probability Ranking Principle for Information Retrieval -- Written Texts as Statistical Mechanical Problem -- What Happened to Content-Based Information Filtering? -- Prior Information and the Determination of Event Spaces in Probabilistic Information Retrieval Models -- Robust Word Similarity Estimation Using Perturbation Kernels -- Possibilistic Similarity Estimation and Visualization -- A New Measure of the Cluster Hypothesis -- Explaining User Performance in Information Retrieval: Challenges to IR Evaluation -- A Four-Factor User Interaction Model for Content-Based Image Retrieval -- Predicting Query Performance by Query-Drift Estimation -- What’s in a Link? From Document Importance to Topical Relevance -- Avoiding Bias in Text Clustering Using Constrained K-means and May-Not-Links -- Optimizing WebPage Interest -- Posters -- The “Beautiful” in Information -- IR Evaluation without a Common Set of Topics -- An Ad Hoc Information Retrieval Perspective on PLSI through Language Model Identification -- Less Is More: Maximal Marginal Relevance as a Summarisation Feature -- On the Notion of “An Information Need” -- A Logical Inference Approach to Query Expansion with Social Tags -- Evaluating Mobile Proactive Context-Aware Retrieval: An Incremental Benchmark -- Predicting the Usefulness of Collection Enrichment for Enterprise Search -- Ranking List Dispersion as a Query Performance Predictor -- Semi-subsumed Events: A Probabilistic Semantics of the BM25 Term Frequency Quantification -- Batch-Mode Computational Advertising Based on Modern Portfolio Theory.