Details
| Originalsprache | Englisch |
|---|---|
| Aufsatznummer | 5710925 |
| Seiten (von - bis) | 426-439 |
| Seitenumfang | 14 |
| Fachzeitschrift | IEEE Transactions on Knowledge and Data Engineering |
| Jahrgang | 24 |
| Ausgabenummer | 3 |
| Publikationsstatus | Veröffentlicht - 6 Feb. 2012 |
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 presents IQ Pa novel approach to bridge the gap between usability of keyword search and expressiveness of database queries. IQ P 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 IQ P include: 1) a probabilistic 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 IQ P, and demonstrates its effectiveness and scalability through experiments over real-world data and a user study.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Information systems
- Informatik (insg.)
- Angewandte Informatik
- Informatik (insg.)
- Theoretische Informatik und Mathematik
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in: IEEE Transactions on Knowledge and Data Engineering, Jahrgang 24, Nr. 3, 5710925, 06.02.2012, S. 426-439.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - A Probabilistic Scheme for Keyword-Based Incremental Query Construction
AU - Demidova, Elena
AU - Zhou, Xuan
AU - Nejdl, Wolfgang
N1 - Funding information: The authors would like to thank Irina Oelze for supporting the implementation of the user study. This work has been partially supported by the FP7 EU Projects OKKAM (contract no. 215032), and ARCOMEM (contract no. 270239), and the “HGJ” Projects of China (grant no.2010ZX01042-001-002).
PY - 2012/2/6
Y1 - 2012/2/6
N2 - 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 presents IQ Pa novel approach to bridge the gap between usability of keyword search and expressiveness of database queries. IQ P 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 IQ P include: 1) a probabilistic 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 IQ P, and demonstrates its effectiveness and scalability through experiments over real-world data and a user study.
AB - 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 presents IQ Pa novel approach to bridge the gap between usability of keyword search and expressiveness of database queries. IQ P 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 IQ P include: 1) a probabilistic 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 IQ P, and demonstrates its effectiveness and scalability through experiments over real-world data and a user study.
KW - Query formulation
KW - search process
UR - http://www.scopus.com/inward/record.url?scp=84863011121&partnerID=8YFLogxK
U2 - 10.1109/TKDE.2011.40
DO - 10.1109/TKDE.2011.40
M3 - Article
AN - SCOPUS:84863011121
VL - 24
SP - 426
EP - 439
JO - IEEE Transactions on Knowledge and Data Engineering
JF - IEEE Transactions on Knowledge and Data Engineering
SN - 1041-4347
IS - 3
M1 - 5710925
ER -