Natural Language Processing and Text Mining (eBook)

Anne Kao, Steve R. Poteet (Herausgeber)

eBook Download: PDF

2007 | 2007
XII, 265 Seiten
Springer London (Verlag)
978-1-84628-754-1 (ISBN)

Infos

Natural Language Processing and Text Mining not only discusses applications of Natural Language Processing techniques to certain Text Mining tasks, but also the converse, the use of Text Mining to assist NLP. It assembles a diverse views from internationally recognized researchers and emphasizes caveats in the attempt to apply Natural Language Processing to text mining. This state-of-the-art survey is a must-have for advanced students, professionals, and researchers.

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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.

Inhalt

Overview.- Extracting Product Features and Opinions from Reviews.- Extracting Relations from Text: From Word Sequences to Dependency Paths.- Mining Diagnostic Text Reports by Learning to Annotate Knowledge Roles.- A Case Study in Natural Language Based Web Search.- Evaluating Self-Explanations in iSTART: Word Matching, Latent Semantic Analysis, and Topic Models.- Textual Signatures: Identifying Text-Types Using Latent Semantic Analysis to Measure the Cohesion of Text Structures.- Automatic Document Separation: A Combination of Probabilistic Classification and Finite-State Sequence Modeling.- Evolving Explanatory Novel Patterns for Semantically-Based Text Mining.- Handling of Imbalanced Data in Text Classification: Category-Based Term Weights.- Automatic Evaluation of Ontologies.- Linguistic Computing with UNIX Tools.

Produkt-Details

• Erscheint lt. Verlag: 6.3.2007
• Zusatzinfo: XII, 265 p.
• Verlagsort: London
• Sprache: englisch
• Themenwelt: Geisteswissenschaften ► Sprach- / Literaturwissenschaft ► Sprachwissenschaft
• Themenwelt: Informatik ► Datenbanken ► Data Warehouse / Data Mining
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Schlagworte: algorithms • classification • Data Mining • latent semantic analysis • learning • linear optimization • machine learning • Matching • Modeling • Natural Language Processing • Processing • Semantic Analysis • service-oriented computing • SIGNATUR • Text Mining • Text-Mining • UNIX
• ISBN-10: 1-84628-754-5 / 1846287545
• ISBN-13: 978-1-84628-754-1 / 9781846287541