In document search, documents are typically seen as a flat list of keywords. To deal with the syntactic interoperability, i.e., the use of different keywords to refer to the same real world entity, entity linkage has been used to replace keywords in the text with a unique identifier of the entity to which they are referring. Yet, the flat list of entities fails to capture the actual relationships that exist among the entities, information that is significant for a more effective document search. In this work we propose to go one step further from entity linkage in text, and model the documents as a set of structures that describe relationships among the entities mentioned in the text. We show that this kind of representation is significantly improving the effectiveness of document search. We describe the details of the implementation of the above idea and we present an extensive set of experimental results that prove our point.
CITATION STYLE
Sartori, E., Velegrakis, Y., & Guerra, F. (2016). Entity-based keyword search in web documents. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9630, 21–49. https://doi.org/10.1007/978-3-662-49521-6_2
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