Parallel co-clustering with augmented matrices algorithm with map-reduce

Meng Lun Wu; Chia Hui Chang

doi:10.1007/978-3-319-10160-6_17

Parallel co-clustering with augmented matrices algorithm with map-reduce

Meng Lun Wu, Chia Hui Chang

Department of Computer Science and Information Engineering

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

3 Scopus citations

Abstract

Co-clustering with augmented matrices (CCAM) [11] is a two-way clustering algorithm that considers dyadic data (e.g., two types of objects) and other correlation data (e.g., objects and their attributes) simultaneously. CCAM was developed to outperform other state-of-the-art algorithms in certain real-world recommendation tasks [12]. However, incorporating multiple correlation data involves a heavy scalability demand. In this paper, we show how the parallel co-clustering with augmented matrices (PCCAM) algorithm can be designed on the Map-Reduce framework. The experimental work shows that the input format, the number of blocks, and the number of reducers can greatly affect the overall performance.

Original language	English
Title of host publication	Data Warehousing and Knowledge Discovery - 16th International Conference, DaWaK 2014, Proceedings
Publisher	Springer Verlag
Pages	183-194
Number of pages	12
ISBN (Print)	9783319101590
DOIs	https://doi.org/10.1007/978-3-319-10160-6_17
State	Published - 2014
Event	16th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2014 - Munich, Germany Duration: 2 Sep 2014 → 4 Sep 2014

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8646 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2014
Country/Territory	Germany
City	Munich
Period	2/09/14 → 4/09/14

Keywords

Co-clustering
Hadoop
Map-Reduce
recommender system

Access to Document

10.1007/978-3-319-10160-6_17

Cite this

Wu, M. L., & Chang, C. H. (2014). Parallel co-clustering with augmented matrices algorithm with map-reduce. In Data Warehousing and Knowledge Discovery - 16th International Conference, DaWaK 2014, Proceedings (pp. 183-194). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8646 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-10160-6_17

Wu, Meng Lun ; Chang, Chia Hui. / Parallel co-clustering with augmented matrices algorithm with map-reduce. Data Warehousing and Knowledge Discovery - 16th International Conference, DaWaK 2014, Proceedings. Springer Verlag, 2014. pp. 183-194 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Wu, ML & Chang, CH 2014, Parallel co-clustering with augmented matrices algorithm with map-reduce. in Data Warehousing and Knowledge Discovery - 16th International Conference, DaWaK 2014, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8646 LNCS, Springer Verlag, pp. 183-194, 16th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2014, Munich, Germany, 2/09/14. https://doi.org/10.1007/978-3-319-10160-6_17

Parallel co-clustering with augmented matrices algorithm with map-reduce. / Wu, Meng Lun; Chang, Chia Hui.
Data Warehousing and Knowledge Discovery - 16th International Conference, DaWaK 2014, Proceedings. Springer Verlag, 2014. p. 183-194 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8646 LNCS).

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

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Wu ML, Chang CH. Parallel co-clustering with augmented matrices algorithm with map-reduce. In Data Warehousing and Knowledge Discovery - 16th International Conference, DaWaK 2014, Proceedings. Springer Verlag. 2014. p. 183-194. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-10160-6_17

Parallel co-clustering with augmented matrices algorithm with map-reduce

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Keywords

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