Abstract
Sifting through vast collections of unstructured or semistructured data beyond the reach of data mining tools, text mining tracks information sources, links isolated concepts in distant documents, maps relationships between activities, and helps answer questions.
- Bollacker, K., Lawrence, S., and Giles, C. A system for automatic personalized tracking of scientific literature on the Web. In Proceedings of the Joint Conference on Digital Libraries (Berkeley, CA). ACM Press, New York, 1999. Google ScholarDigital Library
- ClearForest. ClearForest-Dow Chemical Case Study. ClearForest Corp., Waltham, MA, 2004; www.clearforest.com/Customers/Dow.asp.Google Scholar
- Creese, G. Duo-mining: Combining Data and Text Mining (Sept. 2004); www.dmreview.com/article_sub.cfm?articleId=1010449.Google Scholar
- Gordon, M., Lindsay, R., and Fan, W. Literature-based discovery on the WWW. ACM Transactions on Internet Technology 2, 4 (2002), 262--275. Google ScholarDigital Library
- Han, J., Altman, R., Kumar, V., Mannila, H., and Pregibon, D. Emerging scientific applications in data mining. Commun. ACM 45, 8 (Aug. 2002), 54--58. Google ScholarDigital Library
- Hearst, M. What Is Text Mining?; www.sims.berkeley.edu/~hearst/text-mining.html.Google Scholar
- KartOO Metasearch Engine. KartOO S.A., Clermont Ferrand, France; www.kartoo.com.Google Scholar
- Radev, D., Libner, K., and Fan, W. Getting answers to natural language queries on the Web. Journal of the American Society for Information Science and Technology 53, 5 (2002), 359--364. Google ScholarDigital Library
- Swanson, D. Two medical literatures that are logically but not bibliographically connected. Journal of the American Society for Information Science 38, 4 (1987), 228--233.Google ScholarCross Ref
- Yang, Y. and Pedersen, J. A comparative study on feature selection in text categorization. In Proceedings of the 14th International Conference on Machine Learning. Morgan Kaufmann, San Francisco, 1997, 412--420. Google ScholarDigital Library
Index Terms
- Tapping the power of text mining
Recommendations
Mining Text Using Keyword Distributions
Knowledge Discovery in Databases (KDD) focuses on the computerized exploration of large amounts of data and on the discovery of interesting patterns within them. While most work on KDD has been concerned with structured databases, there has been little work ...
Mining Text Data: Special Features and Patterns
Proceedings of the ESF Exploratory Workshop on Pattern Detection and DiscoveryText mining is an increasingly important research field because of the necessity of obtaining knowledge from the enormous number of text documents available, especially on the Web. Text mining and data mining, both included in the field of information ...
Comments