The purpose of technology watch is to gather, process and integrate the scientific and technical information that is useful to economic players. In this article, we propose to use text mining techniques to automate processing of data found in scientific text databases. The watch activity introduces an unusual difficulty compared with conventional areas of application for text mining techniques since, instead of searching for frequent knowledge hidden in the texts, the target is unexpected knowledge. As a result, the usual measures used for knowledge discovery have to be revised. For that purpose, we have developed the UnexpectedMiner system using new measures for to estimate the unexpectedness of a document. Our system is evaluated using a base that contains articles relating to the field of machine learning. © Springer-Verlag Berlin Heidelberg 2004.
CITATION STYLE
Jacquenet, F., & Largeron, C. (2004). Discovering unexpected information for technology watch. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3202, 219–230. https://doi.org/10.1007/978-3-540-30116-5_22
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