In many contexts today, documents are available in a number of versions. In addition to explicit knowledge that can be queried/searched in documents, these documents also contain implicit knowledge that can be found by text mining. In this paper we will study association rule mining of temporal document collections, and extend previous work within the area by 1) performing mining based on semantics as well as 2) studying the impact of appropriate techniques for ranking of rules. © Springer-Verlag Berlin Heidelberg 2009.
CITATION STYLE
Nørvåg, K., & Fivelstad, O. K. (2009). Semantic-Based temporal text-rule mining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5449 LNCS, pp. 442–455). https://doi.org/10.1007/978-3-642-00382-0_36
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