Practical and effective IR-style keyword search over semantic web
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 263-271 |
| Journal / Publication | Information Processing and Management |
| Volume | 45 |
| Issue number | 2 |
| Publication status | Published - Mar 2009 |
Link(s)
Abstract
This paper presents a novel IR-style keyword search model for semantic web data retrieval, distinguished from current retrieval methods. In this model, an answer to a keyword query is a connected subgraph that contains all the query keywords. In addition, the answer is minimal because any proper subgraph can not be an answer to the query. We provide an approximation algorithm to retrieve these answers efficiently. A special ranking strategy is also proposed so that answers can be appropriately ordered. The experimental results over real datasets show that our model outperforms existing possible solutions with respect to effectiveness and efficiency. © 2009 Elsevier Ltd. All rights reserved.
Research Area(s)
- Group Steiner tree, Keyword search, RDF graph, Top-K
Citation Format(s)
Practical and effective IR-style keyword search over semantic web. / Ning, Xiaomin; Jin, Hai; Jia, Weijia et al.
In: Information Processing and Management, Vol. 45, No. 2, 03.2009, p. 263-271.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
