Survey of Text Mining: Clustering, Classification, and Retrieval

ISBN 10: 1441930574 / ISBN 13: 9781441930576

Editore: Springer, 2011

In. Codice articolo ria9781441930576_new

Riassunto:

As the volume of digitized textual media continues to grow, so does the need for designing robust, scalable indexing and search strategies (software) to meet a variety of user needs. This survey volume draws upon experts in both academia and industry to recommend practical approaches to the purification, indexing, and mining of textual information. Reseachers, practitioners, and professionals in information retrieval who need to know the latest text-mining methods and algorithms will find the book an essential resource.

Dalla quarta di copertina:

 

As the volume of digitized textual information continues to grow, so does the critical need for designing robust and scalable indexing and search strategies/software to meet a variety of user needs. Knowledge extraction or creation from text requires systematic, yet reliable processing that can be codified and adapted for changing needs and environments.

Survey of Text Mining is a comprehensive edited survey organized into three parts: Clustering and Classification; Information Extraction and Retrieval; and Trend Detection. Many of the chapters stress the practical application of software and algorithms for current and future needs in text mining. Authors from industry provide their perspectives on current approaches for large-scale text mining and obstacles that will guide R&D activity in this area for the next decade.

Topics and features:

* Highlights issues such as scalability, robustness, and software tools

* Brings together recent research and techniques from academia and industry

* Examines algorithmic advances in discriminant analysis, spectral clustering, trend detection, and synonym extraction

* Includes case studies in mining Web and customer-support logs for hot- topic extraction and query characterizations

* Extensive bibliography of all references, including websites

This useful survey volume taps the expertise of academicians and industry professionals to recommend practical approaches to purifying, indexing, and mining textual information. Researchers, practitioners, and professionals involved in information retrieval, computational statistics, and data mining, who need the latest text-mining methods and algorithms, will find the book an indispensable resource.

Dati bibliografici

Titolo: Survey of Text Mining: Clustering, ...
Casa editrice: Springer
Data di pubblicazione: 2011
Legatura: Brossura
Condizione: New