2015 | OriginalPaper | Buchkapitel
Effect of Log-Based Query Term Expansion on Retrieval Effectiveness in Patent Searching
verfasst von : Wolfgang Tannebaum, Parvaz Mahdabi, Andreas Rauber
Erschienen in: Experimental IR Meets Multilinguality, Multimodality, and Interaction
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In this paper we study the impact of query term expansion (
QTE
) using synonyms on patent document retrieval. We use an automatically generated lexical database from USPTO query logs, called
PatNet
, which provides synonyms and equivalents for a query term. Our experiments on the CLEF-IP 2010 benchmark dataset show that automatic query expansion using
PatNet
tends to decrease or only slightly improve the retrieval effectiveness, with no significant improvement. An analysis of the retrieval results shows that
PatNet
does not have generally a negative effect on the retrieval effectiveness. Recall is drastically improved for query topics, where the baseline queries achieve, on average, only low recall values. But we have not detected any commonality that allows us to characterize these queries. So we recommend using
PatNet
for semi-automatic
QTE
in Boolean retrieval, where expanding query terms with synonyms and equivalents with the aim of expanding the query scope is a common practice.