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Survey of Text Mining: Clustering, Classification, and Retrieval (No. 1)

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 | #1944214 in Books |  2003-09-09 | Original language:English | PDF # 1 |  9.21 x.63 x6.14l,1.12 | File type: PDF | 244 pages

||0 of 0 people found the following review helpful.| Five Stars|By siamak|excellent old book|0 of 0 people found the following review helpful.| subjective clusters|By W Boudville|The book is relatively brief, given the technical nature of its chapters, each written by different authors. Many clustering methods are described. Most can be seen to have some degree of subjectivity, i|From the Back Cover||  |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 f

Extracting content from text continues to be an important research problem for information processing and management. Approaches to capture the semantics of text-based document collections may be based on Bayesian models, probability theory, vector space models, statistical models, or even graph theory.

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 ...

You easily download any file type for your device.Survey of Text Mining: Clustering, Classification, and Retrieval (No. 1)   |  From Springer. A good, fresh read, highly recommended.

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