Abstract
Patent searching is a complex retrieval task. An initial document search is only the starting point of a chain of searches and decisions that need to be made by patent searchers. Keyword-based retrieval is adequate for document searching, but it is not suitable for modelling comprehensive retrieval strategies. DB-like and logical approaches are the state-of-the-art techniques to model strategies, reasoning and decision making. In this paper we present the application of logical retrieval to patent searching. The two grand challenges are expressiveness and scalability, where high degree of expressiveness usually means a loss in scalability. In this paper we report how to maintain scalability while offering the expressiveness of logical retrieval required for solving patent search tasks. We present logical retrieval background, and how to model data-source selection and results’ fusion. Moreover, we demonstrate the modelling of a retrieval strategy, a technique by which patent professionals are able to express, store and exchange their strategies and rationales when searching patents or when making decisions. An overview of the architecture and technical details complement the paper, while the evaluation reports preliminary results on how query processing times can be guaranteed, and how quality is affected by trading off responsiveness.
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Klampanos, I.A., Wu, H., Roelleke, T., Azzam, H. (2010). Logic-Based Retrieval: Technology for Content-Oriented and Analytical Querying of Patent Data. In: Cunningham, H., Hanbury, A., Rüger, S. (eds) Advances in Multidisciplinary Retrieval. IRFC 2010. Lecture Notes in Computer Science, vol 6107. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13084-7_9
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DOI: https://doi.org/10.1007/978-3-642-13084-7_9
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