Research paper recommander systems: A subspace clustering approach

Nitin Agarwal, Ehtesham Haque, Huan Liu, Lance Parsons

Research output: Chapter in Book/Report/Conference proceedingConference contribution

36 Citations (Scopus)

Abstract

Researchers from the same lab often spend a considerable amount of time searching for published articles relevant to their current project. Despite having similar interests, they conduct independent, time consuming searches. While they may share the results afterwards, they are unable to leverage previous search results during the search process. We propose a research paper recommender system that avoids such time consuming searches by augmenting existing search engines with recommendations based on previous searches performed by others in the lab. Most existing recommender systems were developed for commercial domains with millions of users. The research paper domain has relatively few users compared to the large number of online research papers. The two major challenges with this type of data are the large number of dimensions and the sparseness of the data. The novel contribution of the paper is a scalable subspace clustering algorithm (SCuBA1) that tackles these problems. Both synthetic and benchmark datasets are used to evaluate the clustering algorithm and to demonstrate that it performs better than the traditional collaborative filtering approaches when recommending research papers.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages475-491
Number of pages17
Volume3739 LNCS
StatePublished - 2005
Event6th International Conference on Advances in Web-Age Information Management, WAIM 2005 - Hangzhou, China
Duration: Oct 11 2005Oct 13 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3739 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other6th International Conference on Advances in Web-Age Information Management, WAIM 2005
CountryChina
CityHangzhou
Period10/11/0510/13/05

Fingerprint

Subspace Clustering
Cluster Analysis
Recommender systems
Research
Clustering algorithms
Recommender Systems
Clustering Algorithm
Benchmarking
Search Engine
Collaborative filtering
Search engines
Collaborative Filtering
Leverage
Research Personnel
Recommendations
Benchmark
Evaluate
Demonstrate

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Agarwal, N., Haque, E., Liu, H., & Parsons, L. (2005). Research paper recommander systems: A subspace clustering approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3739 LNCS, pp. 475-491). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3739 LNCS).

Research paper recommander systems : A subspace clustering approach. / Agarwal, Nitin; Haque, Ehtesham; Liu, Huan; Parsons, Lance.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3739 LNCS 2005. p. 475-491 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3739 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Agarwal, N, Haque, E, Liu, H & Parsons, L 2005, Research paper recommander systems: A subspace clustering approach. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 3739 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3739 LNCS, pp. 475-491, 6th International Conference on Advances in Web-Age Information Management, WAIM 2005, Hangzhou, China, 10/11/05.
Agarwal N, Haque E, Liu H, Parsons L. Research paper recommander systems: A subspace clustering approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3739 LNCS. 2005. p. 475-491. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Agarwal, Nitin ; Haque, Ehtesham ; Liu, Huan ; Parsons, Lance. / Research paper recommander systems : A subspace clustering approach. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3739 LNCS 2005. pp. 475-491 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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