TB-Structure: Collective Intelligence for Exploratory Keyword Search

Authors: Vagan, Terziyan; Mariia, Golovianko; Michael, Cochez
Year: 2017
Venue: In: Calì A., Gorgan D., Ugarte M. (eds) Semantic Keyword-Based Search on Structured Data Sources. KEYSTONE 2016. Lecture Notes in Computer Science, vol 10151. Springer, Cham
Link: http://link.springer.com/chapter/10.1007/978-3-319-53640-8_15
Product of the Action: Yes

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In this paper we address an exploratory search challenge by presenting a new (structure-driven) collaborative filtering technique. The aim is to increase search effectiveness by predicting implicit seeker’s intents at an early stage of the search process. This is achieved by uncovering behavioral patterns within large datasets of preserved collective search experience. We apply a specific tree-based data structure called a TB (There-and-Back) structure for compact storage of search history in the form of merged query trails – sequences of queries approaching iteratively a seeker’s goal. The organization of TB-structures allows inferring new implicit trails for the prediction of a seeker’s intents. We used experiments to demonstrate both: the storage compactness and inference potential of the proposed structure.