Text Mining
Predictive Methods for Analyzing Unstructured Information
Text mining searches for regularities, patterns or trends in natural language text. Inspired by data mining, which discovers major patterns from highly structured databases, text mining aims to extract useful knowledge from unstructured text. This book focuses on the concepts and methods needed to expand horizons beyond structured, numeric data to automated mining of text samples. This authoritative and highly accessible text/reference, written by a team of authorities on text mining, develops the foundation concepts, principles, and methods needed to expand beyond structured, numeric data to automated mining of text samples. Researchers, computer scientists, and advanced undergraduates and graduates with work and interests in data mining, machine learning, databases, and computational linguistics will find the work an essential resource.
| Autor: | Damerau, Fred Indurkhya, Nitin Weiss, Sholom M. Zhang, Tong |
|---|---|
| ISBN: | 9780387954332 |
| Sprache: | Englisch |
| Seitenzahl: | 237 |
| Produktart: | Gebunden |
| Verlag: | Springer US |
| Veröffentlicht: | 25.10.2004 |
| Untertitel: | Predictive Methods for Analyzing Unstructured Information |
| Schlagworte: | Active learning Clustering and matching Document classification and correction Extraction Retrieval Summarization classification clustering data mining information retrieval |
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