Page 1
Page 1
Text mining : Predictive methods for analyzing unstructured information
One consequence of the pervasive use of computers is that most documents originate in digital form. Text mining—the process of searching, retrieving, and analyzing unstructured, natural-language text—is concerned with how to exploit the textual data embedded in these documents. Text Mining presents a comprehensive introduction and overview of the field, integrating related topics (such as artificial intelligence and knowledge discovery and data mining) and providing practical advice on how readers can use text-mining methods to analyze their own data. Emphasizing predictive methods, the book unifies all key areas in text mining: preprocessing, text categorization, information search and retrieval, clustering of documents, and information extraction. In addition, it identifies emerging directions for those looking to do research in the area. Some background in data mining is beneficial, but not essential.
Support Vector Machines : Theory and Applications
The support vector machine (SVM) has become one of the standard tools for machine learning and data mining. This carefully edited volume presents the state of the art of the mathematical foundation of SVM in statistical learning theory, as well as novel algorithms and applications. Support Vector Machines provides a selection of numerous real-world applications, such as bioinformatics, text categorization, pattern recognition, and object detection, written by leading experts in the respective fields.
Information retrieval technology ; Vol. 3411 ; Asia information retrieval symposium, AIRS 2004, Beijing, China, October 18-20, 2004. Revised Selected Papers
TheAsiaInformationRetrievalSymposium(AIRS)wasestablishedbytheAsian information retrieval community after the successful series of Information - trieval with Asian Languages (IRAL) workshops held in six di?erent locations in Asia, starting from 1996. While the IRAL workshops had their focus on inf- mation retrieval problems involving Asian languages, AIRS covers a wider scope of applications, systems, technologies and theory aspects of information retrieval in text, audio, image, video and multimedia data. This extension of the scope re?ects and fosters increasing research activities in information retrieval in this region and the growing need for collaborations across subdisciplines. We are very pleased to report that we saw a sharp increase in the number of submissions and their quality, compared to the IRAL workshops. We received 106papersfromninecountriesinAsiaandNorthAmerica,fromwhich28papers (26%) were presented in oral sessions and 38 papers in poster sessions (36%). It was a great challenge for the Program Committee to select the best among the excellent papers. The low acceptance rates witness the success of this year’s conference. After a long discussion between the AIRS 2004 Steering Committee and Springer, the publisher agreed to publish our proceedings in the Lecture Notes in Computer Science (LNCS) series, which is SCI-indexed. We feel that this strongly attests to the excellent quality of the papers.
Information Access through Search Engines and Digital Libraries
he Information Management Systems group at the University of Padua, led by Maristella Agosti, has been a major contributor to information retrieval (IR) and digital libraries for nearly twenty years. This group has gained an excellent reputation in the IR community and has produced some of the best-known IR researchers, whose work spans a broad range of topics.The papers in this book deal with e.g. automated text categorizations, web link analysis algorithms, retrieval in multimedia digital libraries, and multilingual information retrieval. The presentation of original research results built on the past work of the group which at the same time summarizes past .
