Collaborative filtering technique for web service recommendation based on user-operation combination

Nguyen Ngoc Chan; Walid Gaaloul; Samir Tata

doi:10.1007/978-3-642-16934-2_17

Collaborative filtering technique for web service recommendation based on user-operation combination

Nguyen Ngoc Chan
, Walid Gaaloul
, Samir Tata

CNRS UMR 5157 SAMOVAR

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

Abstract

The tremendous growth in the amount of available web services impulses many researchers on proposing recommender systems to help users discover services. Most of the proposed solutions analyzed query strings and web service descriptions to generate recommendations. However, these text-based recommendation approaches depend mainly on user's perspective, languages and notations which easily decrease recommendation's efficiency. In this paper, we present our approach in which we take into account historical usage data instead of the text based analysis. We apply collaborative filtering technique on user's interactions. We propose and implement three algorithms based on Vector Space Model to validate our approach. We also provide evaluation methods based on the precision, recall and root mean square error in order to compare and assert the efficiency of our algorithms.

Original language	English
Title of host publication	On the Move to Meaningful Internet Systems, OTM 2010 - Confederated International Conferences
Subtitle of host publication	CoopIS, IS, DOA and ODBASE, Proceedings
Pages	222-239
Number of pages	18
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-16934-2_17
Publication status	Published - 20 Dec 2010
Event	9th Confederated International Conferences on On the Move to Meaningful Internet Systems, OTM 2010: CoopIS 2010, IS 2010, DOA 2010 and ODBASE 2010 - Crete, Greece Duration: 25 Jan 2010 → 29 Jan 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	6426 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	9th Confederated International Conferences on On the Move to Meaningful Internet Systems, OTM 2010: CoopIS 2010, IS 2010, DOA 2010 and ODBASE 2010
Country/Territory	Greece
City	Crete
Period	25/01/10 → 29/01/10

Keywords

Recommender system
Vector space model
Web service

Access to Document

10.1007/978-3-642-16934-2_17

Cite this

Chan, N. N., Gaaloul, W., & Tata, S. (2010). Collaborative filtering technique for web service recommendation based on user-operation combination. In On the Move to Meaningful Internet Systems, OTM 2010 - Confederated International Conferences: CoopIS, IS, DOA and ODBASE, Proceedings (PART 1 ed., pp. 222-239). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6426 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-16934-2_17

Chan, Nguyen Ngoc ; Gaaloul, Walid ; Tata, Samir. / Collaborative filtering technique for web service recommendation based on user-operation combination. On the Move to Meaningful Internet Systems, OTM 2010 - Confederated International Conferences: CoopIS, IS, DOA and ODBASE, Proceedings. PART 1. ed. 2010. pp. 222-239 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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title = "Collaborative filtering technique for web service recommendation based on user-operation combination",

abstract = "The tremendous growth in the amount of available web services impulses many researchers on proposing recommender systems to help users discover services. Most of the proposed solutions analyzed query strings and web service descriptions to generate recommendations. However, these text-based recommendation approaches depend mainly on user's perspective, languages and notations which easily decrease recommendation's efficiency. In this paper, we present our approach in which we take into account historical usage data instead of the text based analysis. We apply collaborative filtering technique on user's interactions. We propose and implement three algorithms based on Vector Space Model to validate our approach. We also provide evaluation methods based on the precision, recall and root mean square error in order to compare and assert the efficiency of our algorithms.",

keywords = "Recommender system, Vector space model, Web service",

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Chan, NN, Gaaloul, W & Tata, S 2010, Collaborative filtering technique for web service recommendation based on user-operation combination. in On the Move to Meaningful Internet Systems, OTM 2010 - Confederated International Conferences: CoopIS, IS, DOA and ODBASE, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 6426 LNCS, pp. 222-239, 9th Confederated International Conferences on On the Move to Meaningful Internet Systems, OTM 2010: CoopIS 2010, IS 2010, DOA 2010 and ODBASE 2010, Crete, Greece, 25/01/10. https://doi.org/10.1007/978-3-642-16934-2_17

Collaborative filtering technique for web service recommendation based on user-operation combination. / Chan, Nguyen Ngoc; Gaaloul, Walid; Tata, Samir.
On the Move to Meaningful Internet Systems, OTM 2010 - Confederated International Conferences: CoopIS, IS, DOA and ODBASE, Proceedings. PART 1. ed. 2010. p. 222-239 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6426 LNCS, No. PART 1).

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

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AU - Gaaloul, Walid

AU - Tata, Samir

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N2 - The tremendous growth in the amount of available web services impulses many researchers on proposing recommender systems to help users discover services. Most of the proposed solutions analyzed query strings and web service descriptions to generate recommendations. However, these text-based recommendation approaches depend mainly on user's perspective, languages and notations which easily decrease recommendation's efficiency. In this paper, we present our approach in which we take into account historical usage data instead of the text based analysis. We apply collaborative filtering technique on user's interactions. We propose and implement three algorithms based on Vector Space Model to validate our approach. We also provide evaluation methods based on the precision, recall and root mean square error in order to compare and assert the efficiency of our algorithms.

AB - The tremendous growth in the amount of available web services impulses many researchers on proposing recommender systems to help users discover services. Most of the proposed solutions analyzed query strings and web service descriptions to generate recommendations. However, these text-based recommendation approaches depend mainly on user's perspective, languages and notations which easily decrease recommendation's efficiency. In this paper, we present our approach in which we take into account historical usage data instead of the text based analysis. We apply collaborative filtering technique on user's interactions. We propose and implement three algorithms based on Vector Space Model to validate our approach. We also provide evaluation methods based on the precision, recall and root mean square error in order to compare and assert the efficiency of our algorithms.

KW - Recommender system

KW - Vector space model

KW - Web service

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Y2 - 25 January 2010 through 29 January 2010

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Chan NN, Gaaloul W, Tata S. Collaborative filtering technique for web service recommendation based on user-operation combination. In On the Move to Meaningful Internet Systems, OTM 2010 - Confederated International Conferences: CoopIS, IS, DOA and ODBASE, Proceedings. PART 1 ed. 2010. p. 222-239. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-642-16934-2_17

Collaborative filtering technique for web service recommendation based on user-operation combination

Abstract

Publication series

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Keywords

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Cite this