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Advances in Information Retrieval Theory
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 pa...
The Taxobook
This book is the third of a three-part series on taxonomies, and covers putting your taxonomy into use in as many ways as possible to maximize retrieval for your users. Chapter 1 suggests several items to research and consider before you start your implementation and integration process. It explores the different pieces of software that you will need for your system and what features to look for in each. Chapter 2 launches with a discussion of how taxonomy terms can be used within a workflow, connecting two—or more—taxonomies, and intelligent coordination of platforms and taxonomies. Microsoft SharePoint is a widely used and popular program, and I consider their use of taxonomies in this...
Advances in Information Retrieval Theory
This book constitutes the refereed proceedings of the Third International Conference on the Theory of Information Retrieval, ICTIR 2011, held in Bertinoro, Italy, in September 2011. The 25 revised full papers and 13 short papers presented together with the abstracts of two invited talks were carefully reviewed and selected from 65 submissions. The papers cover topics ranging from query expansion, co-occurence analysis, user and interactive modelling, system performance prediction and comparison, and probabilistic approaches for ranking and modelling IR to topics related to interdisciplinary approaches or applications. They are organized into the following topical sections: predicting query performance; latent semantic analysis and word co-occurrence analysis; query expansion and re-ranking; comparison of information retrieval systems and approximate search; probability ranking principle and alternatives; interdisciplinary approaches; user and relevance; result diversification and query disambiguation; and logical operators and descriptive approaches.
Scalable Uncertainty Management
This book constitutes the refereed proceedings of the 4th International Conference on Scalable Uncertainty Management, SUM 2010, held in Toulouse, France, in September 2010. The 26 revised full papers presented together with the abstracts of 2 invited talks and 6 “discussant” contributions were carefully reviewed and selected from 32 submissions. The papers cover all areas of managing substantial and complex kinds of uncertainty and inconsistency in data and knowledge, including applications in decision-support systems, negotiation technologies, semantic web applications, search engines, ontology systems, information retrieval, natural language processing, information extraction, image recognition, vision systems, text mining, and data mining, and consideration of issues such as provenance, trust, heterogeneity, and complexity of data and knowledge.
Risk Assessment and Decision Analysis with Bayesian Networks
Although many Bayesian Network (BN) applications are now in everyday use, BNs have not yet achieved mainstream penetration. Focusing on practical real-world problem solving and model building, as opposed to algorithms and theory, Risk Assessment and Decision Analysis with Bayesian Networks explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide powerful insights and better decision making. Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliabilit...
Information Retrieval Models
Information Retrieval (IR) models are a core component of IR research and IR systems. The past decade brought a consolidation of the family of IR models, which by 2000 consisted of relatively isolated views on TF-IDF (Term-Frequency times Inverse-Document-Frequency) as the weighting scheme in the vector-space model (VSM), the probabilistic relevance framework (PRF), the binary independence retrieval (BIR) model, BM25 (Best-Match Version 25, the main instantiation of the PRF/BIR), and language modelling (LM). Also, the early 2000s saw the arrival of divergence from randomness (DFR). Regarding intuition and simplicity, though LM is clear from a probabilistic point of view, several people state...
Researching Serendipity in Digital Information Environments
Chance, luck, and good fortune are the usual go-to descriptors of serendipity, a phenomenon aptly often coupled with famous anecdotes of accidental discoveries in engineering and science in modern history such as penicillin, Teflon, and Post-it notes. Serendipity, however, is evident in many fields of research, in organizations, in everyday life—and there is more to it than luck implies. While the phenomenon is strongly associated with in person interactions with people, places, and things, most attention of late has focused on its preservation and facilitation within digital information environments. Serendipity's association with unexpected, positive user experiences and outcomes has spu...
Quantifying Research Integrity
Institutions typically treat research integrity violations as black and white, right or wrong. The result is that the wide range of grayscale nuances that separate accident, carelessness, and bad practice from deliberate fraud and malpractice often get lost. This lecture looks at how to quantify the grayscale range in three kinds of research integrity violations: plagiarism, data falsification, and image manipulation. Quantification works best with plagiarism, because the essential one-to-one matching algorithms are well known and established tools for detecting when matches exist. Questions remain, however, of how many matching words of what kind in what location in which discipline constit...
Foundations of Intelligent Systems
This book constitutes the refereed proceedings of the 13th International Symposium on Methodologies for Intelligent Systems, ISMIS 2002, held in Lyon, France, in June 2002. The 63 revised full papers presented were carefully reviewed and selected from around 160 submissions. The book offers topical sections on learning and knowledge discovery, intelligent user interfaces and ontologies, logic for AI, knowledge representation and reasoning, intelligent information retrieval, soft computing, intelligent information systems, and methodologies.
