Approximate Membership Localization within a Web-Based Join Framework
Li, Zhixu, Sitbon, Laurianne, Wang, Liwei, Zhou, Xiaofang, & Du, Xiaoyong (2010) Approximate Membership Localization within a Web-Based Join Framework. In Proceedings of the 19th ACM International Conference on Information and Knowledge Management, ACM.
In this paper, we propose a search-based approach to join two tables in the absence of clean join attributes. Non-structured documents from the web are used to express the correlations between a given query and a reference list. To implement this approach, a major challenge we meet is how to efficiently determine the number of times and the locations of each clean reference from the reference list that is approximately mentioned in the retrieved documents. We formalize the Approximate Membership Localization (AML) problem and propose an efficient partial pruning algorithm to solve it. A study using real-word data sets demonstrates the effectiveness of our search-based approach, and the efficiency of our AML algorithm.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
|Item Type:||Conference Paper|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Deposited On:||30 Aug 2011 05:00|
|Last Modified:||29 Feb 2012 14:27|
Repository Staff Only: item control page