Issue No. 04 - July/August (2006 vol. 10)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MIC.2006.85
Juan José García Adeva , University of Sydney
Rafael A. Calvo , University of Sydney
Information systems are using an increasing amount of unstructured information in the form of text. This situation has spawned a need to improve the text-mining technologies needed for information retrieval, filtering, and classification. This article compares some of the options available and how they can provide textual data-mining functionalities to software applications. In particular, the authors focus on Pimiento, a new object-oriented application framework for text mining. This framework allows developers to easily create distributed applications that use machine learning and statistical techniques to automatically process documents.
text mining, computational linguistics, catgeorization, clustering, information extraction, software frameworks
J. J. García Adeva and R. A. Calvo, "Mining Text with Pimiento," in IEEE Internet Computing, vol. 10, no. , pp. 27-35, 2006.