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This book constitutes the thoroughly refereed proceedings of the 10th Workshop of the Cross Language Evaluation Forum, CLEF 2010, held in Corfu, Greece, in September/October 2009. The volume reports experiments on various types of textual document collections. It is divided into six main sections presenting the results of the following tracks: Multilingual Document Retrieval (Ad-Hoc), Multiple Language Question Answering (QA@CLEF), Multilingual Information Filtering (INFILE@CLEF), Intellectual Property (CLEF-IP) and Log File Analysis (LogCLEF), plus the activities of the MorphoChallenge Program.

Held in Gaithersburg, MD, August November 2-4, 1994. The conference was co-sponsored by the National Inst. of Standards and Technology (NIST) and the Advanced Research Projects Agency (ARPA) and was attended by 150 people involved in the 32 participating groups. Evaluates new technologies in text retrieval. Includes 34 papers: indexing structures, fragmentation schemes, probabilistic retrieval, latent semantic indexing, interactive document retrieval, and much more. Numerous graphs, tables and charts.

This compilation of original papers on information retrieval presents an overview, covering both general theory and specific methods, of the development and current status of information retrieval systems. Each chapter contains several papers carefully chosen to represent substantive research work that has been carried out in that area, each is preceded by an introductory overview and followed by supported references for further reading.

Text mining is a new and exciting area of computer science research that tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. Similarly, link detection – a rapidly evolving approach to the analysis of text that shares and builds upon many of the key elements of text mining – also provides new tools for people to better leverage their burgeoning textual data resources. The Text Mining Handbook presents a comprehensive discussion of the state-of-the-art in text mining and link detection. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, the book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection in such varied fields as M&A business intelligence, genomics research and counter-terrorism activities.

This book constitutes the refereed proceedings of the 10th International Symposium on String Processing and Information Retrieval, SPIRE 2003, held in Manaus, Brazil, in October 2003. The 21 revised full papers and 6 revised short papers presented together with 2 invited papers were carefully reviewed and selected from 54 submissions. The papers are organized in topical sections on Web algorithms, bit-parallel algorithms, compression, categorization and ranking, music retrieval, multilingual information retrieval, subsequences and distributed algorithms, and algorithms on strings and trees.

The last decade has been one of dramatic progress in the field of Natural Language Processing (NLP). This hitherto largely academic discipline has found itself at the center of an information revolution ushered in by the Internet age, as demand for human-computer communication and informa tion access has exploded. Emerging applications in computer-assisted infor mation production and dissemination, automated understanding of news, understanding of spoken language, and processing of foreign languages have given impetus to research that resulted in a new generation of robust tools, systems, and commercial products. Well-positioned government research funding, particularly in the U. S. , has helped to advance the state-of-the art at an unprecedented pace, in no small measure thanks to the rigorous 1 evaluations. This volume focuses on the use of Natural Language Processing in In formation Retrieval (IR), an area of science and technology that deals with cataloging, categorization, classification, and search of large amounts of information, particularly in textual form. An outcome of an information retrieval process is usually a set of documents containing information on a given topic, and may consist of newspaper-like articles, memos, reports of any kind, entire books, as well as annotated image and sound files. Since we assume that the information is primarily encoded as text, IR is also a natural language processing problem: in order to decide if a document is relevant to a given information need, one needs to be able to understand its content.

This new Springer volume provides a comprehensive and detailed look at current approaches to automated question answering. The level of presentation is suitable for newcomers to the field as well as for professionals wishing to study this area and/or to build practical QA systems. The book can serve as a "how-to" handbook for IT practitioners and system developers. It can also be used to teach graduate courses in Computer Science, Information Science and related disciplines.

This book constitutes the refereed proceedings of the Third European Conference on Research and Advanced Technology for Digital Libaries, ECDL'99, held in Paris, France in September 1999. The 26 revised full papers presented were carefully reviewed and selected from a total of 124 submissions. The book is divided in topical sections on image categorization and access, audio and video in digital libraries, information retrieval, user adaptation, knowledge sharing, cross language issues, case studies, and modelling, accessability and connectedness.