Information Retrieval Uncertainty And Logics

In recent years, there have been several attempts to define a logic for information retrieval (IR). The aim was to provide a rich and uniform representation of information and its semantics with the goal of improving retrieval effectiveness. The basis of a logical model for IR is the assumption that queries and documents can be represented effectively by logical formulae. To retrieve a document, an IR system has to infer the formula representing the query from the formula representing the document. This logical interpretation of query and document emphasizes that relevance in IR is an inference process. The use of logic to build IR models enables one to obtain models that are more general than earlier well-known IR models. Indeed, some logical models are able to represent within a uniform framework various features of IR systems such as hypermedia links, multimedia data, and user's knowledge. Logic also provides a common approach to the integration of IR systems with logical database systems. Finally, logic makes it possible to reason about an IR model and its properties. This latter possibility is becoming increasingly more important since conventional evaluation methods, although good indicators of the effectiveness of IR systems, often give results which cannot be predicted, or for that matter satisfactorily explained. However, logic by itself cannot fully model IR. The success or the failure of the inference of the query formula from the document formula is not enough to model relevance in IR. It is necessary to take into account the uncertainty inherent in such an inference process. In 1986, Van Rijsbergen proposed the uncertainty logical principle to model relevance as an uncertain inference process. When proposing the principle, Van Rijsbergen was not specific about which logic and which uncertainty theory to use. As a consequence, various logics and uncertainty theories have been proposed and investigated. The choice of an appropriate logic and uncertainty mechanism has been a main research theme in logical IR modeling leading to a number of logical IR models over the years. Information Retrieval: Uncertainty and Logics contains a collection of exciting papers proposing, developing and implementing logical IR models. This book is appropriate for use as a text for a graduate-level course on Information Retrieval or Database Systems, and as a reference for researchers and practitioners in industry.

Information Retrieval (IR) is concerned with the effective and efficient retrieval of information based on its semantic content. The central problem in IR is the quest to find the set of relevant documents, among a large collection containing the information sought, satisfying a user's information need usually expressed in a natural language query. Documents may be objects or items in any medium: text, image, audio, or indeed a mixture of all three. This book presents 12 revised lectures given at the Third European Summer School in Information Retrieval, ESSIR 2000, held at the Villa Monastero, Varenna, Italy, in September 2000. The first part of the book is devoted to the foundation of IR and related areas; the second part on advanced topics addresses various current issues, from usability aspects to Web searching and browsing.

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.

The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes: - the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning) - the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume 2. AI Algorithms) - the third volume, composed of sixteen chapters, describes the main interfaces and applications of AI (Volume 3. Interfaces and applications of AI). This third volume is dedicated to the interfaces of AI with various fields, with which strong links exist either at the methodological or at the applicative levels. The foreword of this volume reminds us that AI was born for a large part from cybernetics. Chapters are devoted to disciplines that are historically sisters of AI: natural language processing, pattern recognition and computer vision, and robotics. Also close and complementary to AI due to their direct links with information are databases, the semantic web, information retrieval and human-computer interaction. All these disciplines are privileged places for applications of AI methods. This is also the case for bioinformatics, biological modeling and computational neurosciences. The developments of AI have also led to a dialogue with theoretical computer science in particular regarding computability and complexity. Besides, AI research and findings have renewed philosophical and epistemological questions, while their cognitive validity raises questions to psychology. The volume also discusses some of the interactions between science and artistic creation in literature and in music. Lastly, an epilogue concludes the three volumes of this Guided Tour of AI Research by providing an overview of what has been achieved by AI, emphasizing AI as a science, and not just as an innovative technology, and trying to dispel some misunderstandings.

This book constitutes the refereed proceedings of the 5th International Computer Science Conference, ICSC'99, held in Hong Kong, China, in December 1999. The 30 revised full papers presented together with 30 short papers were carefully reviewed and selected from 80 submissions. The book is divided into sections on information filtering, data mining, Web databases, user interfaces, modeling, information retrieval, workflow, applications, active networks, mobility and distributed databases, protocols, distributed systems, information retrieval and filtering, Web technologies, and e-commerce.

This book constitutes the thoroughly refereed post-proceedings of the 2004 International Workshop on Intuitive Human Interfaces for Organizing and Accessing Intellectual Assets, held in Dagstuhl Castle, Germany in March 2004. The 17 revised full papers presented together with an introductory overview have gone through two rounds of reviewing and revision. The papers are organized in topical sections on man-machine interface for intuitive knowledge access, intelligent pad and meme media, visualization and design of information access spaces, and semantics and narrative organization and access of knowledge.

The Semantic Web aims at allowing knowledge to be freely accessed and - changed by software. It is now widely recognized that if the Semantic Web is to contain deep knowledge, the need for new representation and reasoning te- niques is critical. These techniques need to ?nd the right trade-o? between - pressiveness, scalability, and robustness to deal with the inherently incomplete, contradictory, and uncertain nature of knowledge on the Web. The annual International Conference on Web Reasoning and Rule Systems (RR) addresses these needs and has grown into a major international forum for the discussion and dissemination of new results concerning Web Reasoning and Rule Systems. The ?rst three International Conferences on Web Reasoning and Rule Systems (see http://www.rr-conference.org), held in Innsbruck, A- tria (2007), Karlsruhe, Germany (2008), and Chantilly, Virginia, USA (2009), received enthusiastic support from the Web Reasoning community. This volume contains the papers presented at the Fourth International C- ference on Web Reasoning and Rule Systems (RR 2010), which was held in Bressanone/Brixen, Italy, September 22-24, 2010, and which continued the - cellence of the RR series. It contains nine full papers, six short papers, four poster/position papers, one PhD paper, and two system descriptions, which wereselectedoutof31submissionsfollowinga rigorousreviewingprocess,where each submission was reviewed by at least three program committee members. The volumealso containsextended abstractsof the threeinvited talks/tutorials.

This book presents revised full papers from the 10th International Workshop on Logic-Based Program Synthesis and Transformation, LOPSTR 2000, held in London, UK, in July 2000 as part of the International Conference on Computational Logic. The 10 revised full papers presented have gone through two rounds of reviewing, selection and revision. The book is divided in topical sections on synthesis, transformation, analysis, specialization, and abstract interpretation.