Refining search results using a mining framework
Expert Systems with Applications: An International Journal
A comparative study of TF*IDF, LSI and multi-words for text classification
Expert Systems with Applications: An International Journal
The GIL summarizers: experiments in the track QA@INEX'10
INEX'10 Proceedings of the 9th international conference on Initiative for the evaluation of XML retrieval: comparative evaluation of focused retrieval
Improving automated documentation to code traceability by combining retrieval techniques
ASE '11 Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering
PRETO: a high-performance text mining tool for preprocessing Turkish texts
Proceedings of the 13th International Conference on Computer Systems and Technologies
Competence maps using agglomerative hierarchical clustering
Journal of Intelligent Manufacturing
Simulating the spread of opinions in online social networks when targeting opinion leaders
Information Systems and e-Business Management
BizPro: Extracting and categorizing business intelligence factors from textual news articles
International Journal of Information Management: The Journal for Information Professionals
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The growth of the web can be seen as an expanding public digital library collection. Online digital information extends far beyond the web and its publicly available information. Huge amounts of information are private and are of interest to local communities, such as the records of customers of a business. This information is overwhelmingly text and has its record-keeping purpose, but an automated analysis might be desirable to find patterns in the stored records. Analogous to this data mining is text mining, which also finds patterns and trends in information samples but which does so with far less structured--though with greater immediate utility for users--ingredients. This book focuses on the concepts and methods needed to expand horizons beyond structured, numeric data to automated mining of text samples. It introduces the new world of text mining and examines proven methods for various critical text-mining tasks, such as automated document indexing and information retrieval and search. New research areas are explored, such as information extraction and document summarization, that rely on evolving text-mining techniques.