SimSeerX: A similar document search engine

Kyle Williams; Jian Wu; C. Lee Giles

doi:10.1145/2644866.2644895

SimSeerX: A similar document search engine

Kyle Williams, Jian Wu, C. Lee Giles

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

11 Scopus citations

Abstract

The need to find similar documents occurs in many settings, such as in plagiarism detection or research paper recommendation. Manually constructing queries to find similar documents may be overly complex, thus motivating the use of whole documents as queries. This paper introduces Sim-SeerX, a search engine for similar document retrieval that receives whole documents as queries and returns a ranked list of similar documents. Key to the design of SimSeerX is that is able to work with multiple similarity functions and document collections. We present the architecture and interface of SimSeerX, show its applicability with 3 different similarity functions and demonstrate its scalability on a collection of 3.5 million academic documents.

Original language	English (US)
Title of host publication	DocEng 2014 - Proceedings of the 2014 ACM Symposium on Document Engineering
Publisher	Association for Computing Machinery, Inc
Pages	143-146
Number of pages	4
ISBN (Electronic)	9781450329491
DOIs	https://doi.org/10.1145/2644866.2644895
State	Published - 2014
Event	2014 ACM Symposium on Document Engineering, DocEng 2014 - Fort Collins, United States Duration: Sep 16 2014 → Sep 19 2014

Publication series

Name	DocEng 2014 - Proceedings of the 2014 ACM Symposium on Document Engineering

Other

Other	2014 ACM Symposium on Document Engineering, DocEng 2014
Country/Territory	United States
City	Fort Collins
Period	9/16/14 → 9/19/14

All Science Journal Classification (ASJC) codes

Software
Information Systems
Computer Science Applications

Access to Document

10.1145/2644866.2644895

Cite this

@inproceedings{a0891ee21a6f468599707a435bc8e0d3,

title = "SimSeerX: A similar document search engine",

abstract = "The need to find similar documents occurs in many settings, such as in plagiarism detection or research paper recommendation. Manually constructing queries to find similar documents may be overly complex, thus motivating the use of whole documents as queries. This paper introduces Sim-SeerX, a search engine for similar document retrieval that receives whole documents as queries and returns a ranked list of similar documents. Key to the design of SimSeerX is that is able to work with multiple similarity functions and document collections. We present the architecture and interface of SimSeerX, show its applicability with 3 different similarity functions and demonstrate its scalability on a collection of 3.5 million academic documents.",

author = "Kyle Williams and Jian Wu and Giles, {C. Lee}",

note = "Publisher Copyright: {\textcopyright} 2014 ACM.; 2014 ACM Symposium on Document Engineering, DocEng 2014 ; Conference date: 16-09-2014 Through 19-09-2014",

year = "2014",

doi = "10.1145/2644866.2644895",

language = "English (US)",

series = "DocEng 2014 - Proceedings of the 2014 ACM Symposium on Document Engineering",

publisher = "Association for Computing Machinery, Inc",

pages = "143--146",

booktitle = "DocEng 2014 - Proceedings of the 2014 ACM Symposium on Document Engineering",

}

Williams, K, Wu, J & Giles, CL 2014, SimSeerX: A similar document search engine. in DocEng 2014 - Proceedings of the 2014 ACM Symposium on Document Engineering. DocEng 2014 - Proceedings of the 2014 ACM Symposium on Document Engineering, Association for Computing Machinery, Inc, pp. 143-146, 2014 ACM Symposium on Document Engineering, DocEng 2014, Fort Collins, United States, 9/16/14. https://doi.org/10.1145/2644866.2644895

SimSeerX: A similar document search engine. / Williams, Kyle; Wu, Jian; Giles, C. Lee.
DocEng 2014 - Proceedings of the 2014 ACM Symposium on Document Engineering. Association for Computing Machinery, Inc, 2014. p. 143-146 (DocEng 2014 - Proceedings of the 2014 ACM Symposium on Document Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T2 - 2014 ACM Symposium on Document Engineering, DocEng 2014

AU - Williams, Kyle

AU - Wu, Jian

AU - Giles, C. Lee

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N2 - The need to find similar documents occurs in many settings, such as in plagiarism detection or research paper recommendation. Manually constructing queries to find similar documents may be overly complex, thus motivating the use of whole documents as queries. This paper introduces Sim-SeerX, a search engine for similar document retrieval that receives whole documents as queries and returns a ranked list of similar documents. Key to the design of SimSeerX is that is able to work with multiple similarity functions and document collections. We present the architecture and interface of SimSeerX, show its applicability with 3 different similarity functions and demonstrate its scalability on a collection of 3.5 million academic documents.

AB - The need to find similar documents occurs in many settings, such as in plagiarism detection or research paper recommendation. Manually constructing queries to find similar documents may be overly complex, thus motivating the use of whole documents as queries. This paper introduces Sim-SeerX, a search engine for similar document retrieval that receives whole documents as queries and returns a ranked list of similar documents. Key to the design of SimSeerX is that is able to work with multiple similarity functions and document collections. We present the architecture and interface of SimSeerX, show its applicability with 3 different similarity functions and demonstrate its scalability on a collection of 3.5 million academic documents.

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M3 - Conference contribution

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BT - DocEng 2014 - Proceedings of the 2014 ACM Symposium on Document Engineering

PB - Association for Computing Machinery, Inc

Y2 - 16 September 2014 through 19 September 2014

ER -

SimSeerX: A similar document search engine

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

Access to Document

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