Approximate Membership Localization (AML) for web-based join

Zhixu Li; Laurianne Sitbon; Liwei Wang; Xiaofang Zhou; Xiaoyong Du

doi:10.1145/1871437.1871611

Approximate Membership Localization (AML) for web-based join

Zhixu Li^*, Laurianne Sitbon, Liwei Wang, Xiaofang Zhou, Xiaoyong Du

^*Corresponding author for this work

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

2 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops
Pages	1321-1324
Number of pages	4
DOIs	https://doi.org/10.1145/1871437.1871611
Publication status	Published - 2010
Externally published	Yes
Event	19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10 - Toronto, ON, Canada Duration: 26 Oct 2010 → 30 Oct 2010

Publication series

Name	International Conference on Information and Knowledge Management, Proceedings

Conference

Conference	19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10
Country/Territory	Canada
City	Toronto, ON
Period	26/10/10 → 30/10/10

Keywords

AML
Approximate join
Approximate membership location
Web-based join

Access to Document

10.1145/1871437.1871611

Cite this

Li, Z., Sitbon, L., Wang, L., Zhou, X., & Du, X. (2010). Approximate Membership Localization (AML) for web-based join. In CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops (pp. 1321-1324). (International Conference on Information and Knowledge Management, Proceedings). https://doi.org/10.1145/1871437.1871611

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title = "Approximate Membership Localization (AML) for web-based join",

abstract = "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.",

keywords = "AML, Approximate join, Approximate membership location, Web-based join",

author = "Zhixu Li and Laurianne Sitbon and Liwei Wang and Xiaofang Zhou and Xiaoyong Du",

year = "2010",

doi = "10.1145/1871437.1871611",

language = "English",

isbn = "9781450300995",

series = "International Conference on Information and Knowledge Management, Proceedings",

pages = "1321--1324",

booktitle = "CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops",

note = "19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10 ; Conference date: 26-10-2010 Through 30-10-2010",

}

Li, Z, Sitbon, L, Wang, L, Zhou, X & Du, X 2010, Approximate Membership Localization (AML) for web-based join. in CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops. International Conference on Information and Knowledge Management, Proceedings, pp. 1321-1324, 19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10, Toronto, ON, Canada, 26/10/10. https://doi.org/10.1145/1871437.1871611

Approximate Membership Localization (AML) for web-based join. / Li, Zhixu; Sitbon, Laurianne; Wang, Liwei et al.
CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops. 2010. p. 1321-1324 (International Conference on Information and Knowledge Management, Proceedings).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

TY - GEN

T1 - Approximate Membership Localization (AML) for web-based join

AU - Li, Zhixu

AU - Sitbon, Laurianne

AU - Wang, Liwei

AU - Zhou, Xiaofang

AU - Du, Xiaoyong

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

KW - AML

KW - Approximate join

KW - Approximate membership location

KW - Web-based join

UR - https://openalex.org/W2084868841

UR - https://www.scopus.com/pages/publications/78651275614

U2 - 10.1145/1871437.1871611

DO - 10.1145/1871437.1871611

M3 - Conference Paper published in a book

SN - 9781450300995

T3 - International Conference on Information and Knowledge Management, Proceedings

SP - 1321

EP - 1324

BT - CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops

T2 - 19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10

Y2 - 26 October 2010 through 30 October 2010

ER -

Approximate Membership Localization (AML) for web-based join

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