Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.is.2008.08.001
Title: An effective 3-in-1 keyword search method over heterogeneous data sources
Authors: Li, G.
Feng, J.
Chin Ooi, B. 
Wang, J.
Zhou, L.
Keywords: Extended inverted index
Graph index
Inverted index
Keyword search
Ranking
Semi-structured data
Structured data
Unstructured data
Issue Date: 2011
Source: Li, G., Feng, J., Chin Ooi, B., Wang, J., Zhou, L. (2011). An effective 3-in-1 keyword search method over heterogeneous data sources. Information Systems 36 (2) : 248-266. ScholarBank@NUS Repository. https://doi.org/10.1016/j.is.2008.08.001
Abstract: Conventional keyword search engines are restricted to a given data model and cannot easily adapt to unstructured, semi-structured or structured data. In this paper, we propose an efficient and adaptive keyword search method, called EASE, for indexing and querying large collections of heterogeneous data. To achieve high efficiency in processing keyword queries, we first model unstructured, semi-structured and structured data as graphs, and then summarize the graphs and construct graph indices instead of using traditional inverted indices. We propose an extended inverted index to facilitate keyword-based search, and present a novel ranking mechanism for enhancing search effectiveness. We have conducted an extensive experimental study using real datasets, and the results show that EASE achieves both high search efficiency and high accuracy, and outperforms the existing approaches significantly. © 2008 Elsevier B.V. All rights reserved.
Source Title: Information Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/39096
ISSN: 03064379
DOI: 10.1016/j.is.2008.08.001
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

8
checked on Dec 7, 2017

WEB OF SCIENCETM
Citations

7
checked on Nov 29, 2017

Page view(s)

53
checked on Dec 4, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.