@inproceedings{5181b2cff80948a9ae69b96676080632,
title = "TB-structure: Collective intelligence for exploratory keyword search",
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{\textquoteright}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{\textquoteright}s goal. The organization of TB-structures allows inferring new implicit trails for the prediction of a seeker{\textquoteright}s intents. We used experiments to demonstrate both: the storage compactness and inference potential of the proposed structure.",
keywords = "Collective intelligence, Query trail, Search, TB-structure",
author = "Vagan Terziyan and Mariia Golovianko and Michael Cochez",
year = "2017",
month = jan,
day = "1",
doi = "10.1007/978-3-319-53640-8_15",
language = "English",
isbn = "9783319536392",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "171--178",
editor = "Andrea Cali and Dorian Gorgan and Martin Ugarte",
booktitle = "Semantic Keyword-Based Search on Structured Data Sources - COST Action IC1302 2nd International KEYSTONE Conference, IKC 2016, Revised Selected Papers",
address = "Germany",
note = "2nd COST Action IC1302 International KEYSTONE Conference on Semantic Keyword-Based Search on Structured Data Sources, IKC 2016 ; Conference date: 08-09-2016 Through 09-09-2016",
}