Exploratory Patent Search with Faceted Search and Configurable Entity Mining

Searching for patents is usually a recall-oriented problem and depending on the patent search type, quite often a problem which is characterized by uncertainty and evolution or change of the information need. We propose an exploratory strategy for patent search that exploits the metadata already available in patents in addition to the results of clustering and entity mining that are performed at query time. The results (metadata, clusters and entities grouped in categories) can complement the ranked list of patents produced from the core search engine with useful information for the user (e.g. providing a concise overview of the search results) which are further exploited in a faceted and sessionbased interaction scheme that allows the users to focus their searches gradually and to change between search methods as their information need is better defined and their understanding of the topic evolves in response to found information. In addition, we propose the exploitation of Linked Data for specifying the entities of interest and for providing further information about the identified entities. The proposed system offers a dynamic, entity-based integration of patent documents, patents metadata and other external (semantic) resources.