Abstract
This paper outlines our participation in CLEF-IP's 2009 prior art search task. In the task's initial year our focus lay on the automatic generation of effective queries. To this aim we conducted a preliminary analysis of the distribution of terms common to topics and their relevant documents, with respect to term frequency and document frequency. Based on the results of this analysis we applied two methods to extract queries. Finally we tested the effectiveness of the generated queries on two state of the art retrieval models. © 2010 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Graf, E., Azzopardi, L., & Van Rijsbergen, K. (2010). Automatically generating queries for prior art search. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6241 LNCS, pp. 480–490). https://doi.org/10.1007/978-3-642-15754-7_58
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