Details
Originalsprache | Englisch |
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Titel des Sammelwerks | Database and Expert Systems Applications - 21st International Conference, DEXA 2010, Proceedings |
Seiten | 240-247 |
Seitenumfang | 8 |
Auflage | PART 2 |
Publikationsstatus | Veröffentlicht - 8 Nov. 2010 |
Veranstaltung | 21st International Conference on Database and Expert Systems Applications, DEXA 2010 - Bilbao, Spanien Dauer: 30 Aug. 2010 → 3 Sept. 2010 |
Publikationsreihe
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Nummer | PART 2 |
Band | 6262 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (elektronisch) | 1611-3349 |
Abstract
A number of existing approaches attempt to reduce ambiguity of user's keyword queries by translating them to structured database queries. This disambiguation process relies on a proper assessment of whether a structured query represents the intent behind the keyword query. In this paper we systematically analyze a number of intuitive statistical measures that can potentially be used in this disambiguation process. We evaluate the impact of these measures through experiments on real-world data.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Theoretische Informatik
- Informatik (insg.)
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Database and Expert Systems Applications - 21st International Conference, DEXA 2010, Proceedings. PART 2. Aufl. 2010. S. 240-247 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 6262 LNCS, Nr. PART 2).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Evaluating Evidences for Keyword Query Disambiguation in Entity Centric Database Search
AU - Demidova, Elena
AU - Zhou, Xuan
AU - Oelze, Irina
AU - Nejdl, Wolfgang
PY - 2010/11/8
Y1 - 2010/11/8
N2 - A number of existing approaches attempt to reduce ambiguity of user's keyword queries by translating them to structured database queries. This disambiguation process relies on a proper assessment of whether a structured query represents the intent behind the keyword query. In this paper we systematically analyze a number of intuitive statistical measures that can potentially be used in this disambiguation process. We evaluate the impact of these measures through experiments on real-world data.
AB - A number of existing approaches attempt to reduce ambiguity of user's keyword queries by translating them to structured database queries. This disambiguation process relies on a proper assessment of whether a structured query represents the intent behind the keyword query. In this paper we systematically analyze a number of intuitive statistical measures that can potentially be used in this disambiguation process. We evaluate the impact of these measures through experiments on real-world data.
KW - entity search
KW - keyword query disambiguation
KW - statistical analysis
UR - http://www.scopus.com/inward/record.url?scp=78049375334&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-15251-1_19
DO - 10.1007/978-3-642-15251-1_19
M3 - Conference contribution
AN - SCOPUS:78049375334
SN - 3642152503
SN - 9783642152504
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 240
EP - 247
BT - Database and Expert Systems Applications - 21st International Conference, DEXA 2010, Proceedings
T2 - 21st International Conference on Database and Expert Systems Applications, DEXA 2010
Y2 - 30 August 2010 through 3 September 2010
ER -