Survey of Text Mining: Clustering, Classification, and Retrieval 2004th Edition by Michael W. Berry (PDF)

Description

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.This book will draw upon experts in both academia and industry to recommend practical approaches to the purification, indexing, and mining of textual information. It will address document identification, clustering and categorizing documents, cleaning text, and visualizing semantic models of text.

User’s Reviews

Editorial Reviews: 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 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 websitesThis 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.

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐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, in defining what ends up in a given cluster. Or whether a cluster even exists or not.The analysis of Web documents forms a major portion of the book. This data set is vast, continually changing and expanding. Plus, it is noisy. Unlike many clean data sets that might be extracted from a corpus of books, for example. Attention should be paid to methods of automatically extracting information from the Web.The book does not go much into the higher level problems of defining ontologies. Which are very hard tasks. The closest it seems to get is along the lines of finding similar words in documents. Which is still very useful.

⭐excellent old book

⭐book was so old …

Keywords

Free Download Survey of Text Mining: Clustering, Classification, and Retrieval 2004th Edition in PDF format
Survey of Text Mining: Clustering, Classification, and Retrieval 2004th Edition PDF Free Download
Download Survey of Text Mining: Clustering, Classification, and Retrieval 2004th Edition 2004 PDF Free
Survey of Text Mining: Clustering, Classification, and Retrieval 2004th Edition 2004 PDF Free Download
Download Survey of Text Mining: Clustering, Classification, and Retrieval 2004th Edition PDF
Free Download Ebook Survey of Text Mining: Clustering, Classification, and Retrieval 2004th Edition