![Survey of Text Mining. Clustering, Classification, and Retrieval](/uploads/posts/2021-02/1613320097_fa9906f48cf6b5c4f27cafc2291f55e8_250.jpg)
Название: Survey of Text Mining. Clustering, Classification, and Retrieval
Автор: Michael W. Berry
Издательство: Springer
Год: 2003
Формат: pdf
Страниц: 262
Размер: 10 Mb
Язык: English
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 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.