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001 978-1-84628-754-1
003 DE-He213
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008 100301s2007 xxk| s |||| 0|eng d
020 _a9781846287541
_9978-1-84628-754-1
024 7 _a10.1007/978-1-84628-754-1
_2doi
050 4 _aQA75.5-76.95
072 7 _aUNH
_2bicssc
072 7 _aUND
_2bicssc
072 7 _aCOM030000
_2bisacsh
082 0 4 _a025.04
_223
100 1 _aKao, Anne.
_eeditor.
245 1 0 _aNatural Language Processing and Text Mining
_h[electronic resource] /
_cedited by Anne Kao, Stephen R. Poteet.
264 1 _aLondon :
_bSpringer London,
_c2007.
300 _aXII, 265 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aOverview -- 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.
520 _aWith 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 world problems. In addition, it can be used as a supplementary text for advanced students studying text mining and NLP.
650 0 _aComputer science.
650 0 _aInformation theory.
650 0 _aInformation storage and retrieval systems.
650 0 _aInformation systems.
650 0 _aElectronic data processing.
650 1 4 _aComputer Science.
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aComputing Methodologies.
650 2 4 _aProcessor Architectures.
650 2 4 _aTheory of Computation.
650 2 4 _aInformation Systems Applications (incl.Internet).
650 2 4 _aComputer Appl. in Administrative Data Processing.
700 1 _aPoteet, Stephen R.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781846281754
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-84628-754-1
912 _aZDB-2-SCS
999 _c17323
_d17323