Natural Language Processing and Text Mining

The topic this book addresses originated from a panel discussion at the 2004 ACM SIGKDD (Special Interest Group on Knowledge Discovery and Data Mining) Conference held in Seattle, Washington, USA. At the same time, Springer believed this to be a topic of wide interest and expressed an interest in seeing a book published. With the increasing importance of the Web and other text-heavy application areas, the demands for and interest in both text mining and natural language processing (NLP) have been rising. Researchers in text mining have hoped that NLP—the attempt to extract a fuller meaning representation from free text—can provide useful improvements to text mining applications of all kinds. Bringing together a variety of perspectives from internationally renowned researchers, Natural Language Processing and Text Mining not only discusses applications of certain NLP techniques to certain Text Mining tasks, but also the converse, i.e., use of Text Mining to facilitate NLP. It explores a variety of real-world applications of NLP and text-mining algorithms in comprehensive detail, placing emphasis on the description of end-to-end solutions to real problems, and detailing the associated difficulties that must be resolved before the algorithm can be applied and its full benefits realized. In addition, it explores a number of cutting-edge techniques and approaches, as well as novel ways of integrating various technologies. Nevertheless, even readers with only a basic knowledge of data mining or text mining will benefit from the many illustrative examples and solutions. Topics and features: • Describes novel and high-impact text mining and/or natural language applications • Points out typical traps in trying to apply NLP to text mining • Illustrates preparation and preprocessing of text data – offering practical issues and examples • Surveys related supporting techniques, problem types, and potential technique enhancements • Examines the interaction of text mining and NLP This state-of-the-art, practical volume will be an essential resource for professionals and researchers who wish to learn how to apply text mining and language processing techniques to real worldproblems. In addition, it can be used as a supplementary text for advanced students studying text mining and NLP. The topic this book addresses originated from a panel discussion at the 2004 ACM SIGKDD (Special Interest Group on Knowledge Discovery and Data Mining) Conference held in Seattle, Washington, USA. We the editors or- nized the panel to promote discussion on how text mining and natural l- guageprocessing,tworelatedtopicsoriginatingfromverydi?erentdisciplines, can best interact with each other, and bene?t from each other’s strengths. It attracted a great deal of interest and was attended by 200 people from all over the world. We then guest-edited a special issue of ACM SIGKDD Exp- rations on the same topic, with a number of very interesting papers. At the same time, Springer believed this to be a topic of wide interest and expressed an interest in seeing a book published. After a year of work, we have put - gether 11 papers from international researchers on a range of techniques and applications. We hope this book includes papers readers do not normally ?nd in c- ference proceedings, which tend to focus more on theoretical or algorithmic breakthroughs but are often only tried on standard test data. We would like to provide readers with a wider range of applications, give some examples of the practical application of algorithms on real-world problems, as well as share a number of useful techniques.