IQ^P: Incremental Query Construction, a Probabilistic Approach
E. Demidova, X. Zhou, and W. Nejdl. Proceedings of the 26th IEEE International Conference on Data Engineering, ICDE 2010, Long Beach, California, USA, March 1-6, 2010, IEEE, (2010)
DOI: 10.1109/ICDE.2010.5447929
Abstract
Databases enable users to precisely express their informational needs using structured queries. However, database query construction is a laborious and error-prone process, which cannot be performed well by most end users. Keyword search alleviates the usability problem at the price of query expressiveness. As keyword search algorithms do not differentiate between the possible informational needs represented by a keyword query, users may not receive adequate results. This paper proposes IQP - a novel approach to bridge the gap between usability of keyword search and expressiveness of database queries. IQP enables a user to start with an arbitrary keyword query and incrementally refine it into a structured query through an interactive interface. The enabling techniques of IQP include: (1) a conceptual framework for incremental query construction; (2) a probabilistic model to assess the possible informational needs represented by a keyword query; (3) an algorithm to obtain the optimal query construction process. This paper presents the detailed design of IQP, and demonstrates its effectiveness through experiments over real-world data.
%0 Conference Paper
%1 demidova10icde
%A Demidova, Elena
%A Zhou, Xuan
%A Nejdl, Wolfgang
%B Proceedings of the 26th IEEE International Conference on Data Engineering, ICDE 2010, Long Beach, California, USA, March 1-6, 2010
%D 2010
%E Li, Feifei
%E Moro, Mirella M.
%E Ghandeharizadeh, Shahram
%E Haritsa, Jayant R.
%E Weikum, Gerhard
%E Carey, Michael J.
%E Casati, Fabio
%E Chang, Edward Y.
%E Manolescu, Ioana
%E Mehrotra, Sharad
%E Dayal, Umeshwar
%E Tsotras, Vassilis J.
%I IEEE
%K construction keyword myown okkam query
%R 10.1109/ICDE.2010.5447929
%T IQ^P: Incremental Query Construction, a Probabilistic Approach
%U http://dblp.uni-trier.de/db/conf/icde/icde2010.html#DemidovaZN10
%X Databases enable users to precisely express their informational needs using structured queries. However, database query construction is a laborious and error-prone process, which cannot be performed well by most end users. Keyword search alleviates the usability problem at the price of query expressiveness. As keyword search algorithms do not differentiate between the possible informational needs represented by a keyword query, users may not receive adequate results. This paper proposes IQP - a novel approach to bridge the gap between usability of keyword search and expressiveness of database queries. IQP enables a user to start with an arbitrary keyword query and incrementally refine it into a structured query through an interactive interface. The enabling techniques of IQP include: (1) a conceptual framework for incremental query construction; (2) a probabilistic model to assess the possible informational needs represented by a keyword query; (3) an algorithm to obtain the optimal query construction process. This paper presents the detailed design of IQP, and demonstrates its effectiveness through experiments over real-world data.
@inproceedings{demidova10icde,
abstract = {Databases enable users to precisely express their informational needs using structured queries. However, database query construction is a laborious and error-prone process, which cannot be performed well by most end users. Keyword search alleviates the usability problem at the price of query expressiveness. As keyword search algorithms do not differentiate between the possible informational needs represented by a keyword query, users may not receive adequate results. This paper proposes IQP - a novel approach to bridge the gap between usability of keyword search and expressiveness of database queries. IQP enables a user to start with an arbitrary keyword query and incrementally refine it into a structured query through an interactive interface. The enabling techniques of IQP include: (1) a conceptual framework for incremental query construction; (2) a probabilistic model to assess the possible informational needs represented by a keyword query; (3) an algorithm to obtain the optimal query construction process. This paper presents the detailed design of IQP, and demonstrates its effectiveness through experiments over real-world data. },
added-at = {2013-04-24T12:24:50.000+0200},
author = {Demidova, Elena and Zhou, Xuan and Nejdl, Wolfgang},
biburl = {https://www.bibsonomy.org/bibtex/25f6490f6eac32d46c05ec0cd1319e53a/demidova},
booktitle = {Proceedings of the 26th IEEE International Conference on Data Engineering, ICDE 2010, Long Beach, California, USA, March 1-6, 2010},
copyright = {2010 IEEE},
doi = {10.1109/ICDE.2010.5447929},
editor = {Li, Feifei and Moro, Mirella M. and Ghandeharizadeh, Shahram and Haritsa, Jayant R. and Weikum, Gerhard and Carey, Michael J. and Casati, Fabio and Chang, Edward Y. and Manolescu, Ioana and Mehrotra, Sharad and Dayal, Umeshwar and Tsotras, Vassilis J.},
interhash = {e7128959ed73b88b04a73af0c3cb2a4a},
intrahash = {5f6490f6eac32d46c05ec0cd1319e53a},
keywords = {construction keyword myown okkam query},
publisher = {IEEE},
timestamp = {2016-04-24T23:03:54.000+0200},
title = {IQ^P: Incremental Query Construction, a Probabilistic Approach},
url = {http://dblp.uni-trier.de/db/conf/icde/icde2010.html#DemidovaZN10},
year = 2010
}