A4 Article in conference proceedings
TB-Structure : Collective Intelligence for Exploratory Keyword Search (2017)


Terziyan, V., Golovianko, M., & Cochez, M. (2017). TB-Structure : Collective Intelligence for Exploratory Keyword Search. In A. Calì, D. Gorgan, & M. Ugarte (Eds.), Semantic Keyword-Based Search on Structured Data Sources. COST Action IC1302 Second International KEYSTONE Conference, IKC 2016, Cluj-Napoca, Romania, September 8–9, 2016, Revised Selected Papers (pp. 171-178). Springer International Publishing. Lecture Notes in Computer Science, 10151. https://doi.org/10.1007/978-3-319-53640-8_15


JYU authors or editors


Publication details

All authors or editors: Terziyan, Vagan; Golovianko, Mariia; Cochez, Michael

Parent publication: Semantic Keyword-Based Search on Structured Data Sources. COST Action IC1302 Second International KEYSTONE Conference, IKC 2016, Cluj-Napoca, Romania, September 8–9, 2016, Revised Selected Papers

Parent publication editors: Calì, Andrea; Gorgan, Dorian; Ugarte, Martín

Conference:

  • International keystone conference

ISBN: 978-3-319-53639-2

Journal or series: Lecture Notes in Computer Science

ISSN: 0302-9743

Publication year: 2017

Number in series: 10151

Pages range: 171-178

Publisher: Springer International Publishing

Publication country: Switzerland

Publication language: English

DOI: https://doi.org/10.1007/978-3-319-53640-8_15

Publication open access: Not open

Publication channel open access: 

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/55916

Additional information: COST Action IC1302 Second International KEYSTONE Conference, IKC 2016, Cluj-Napoca, Romania, September 8–9, 2016, Revised Selected Papers.


Abstract

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.
See presentation slides: https://ai.it.jyu.fi/IKC-2016.pptx


Keywords: collective intelligence

Free keywords: keyword search; query trail; TB-structure


Contributing organizations


Ministry reporting: Yes

VIRTA submission year: 2017

JUFO rating: 0


Last updated on 2024-11-05 at 20:25