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A recommender system based on historical usage data for web service discovery

Authors:

Nguyen Ngoc Chan,

Samir TataAuthors Info & Claims

Service Oriented Computing and Applications, Volume 6, Issue 1

Pages 51 - 63

https://doi.org/10.1007/s11761-011-0099-2

Published: 01 March 2012 Publication History

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 an 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 four algorithms to validate our approach. We also provide evaluation methods based on the precision and recall in order to assert the efficiency of our algorithms.

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Cited By

Hu QQi HHuang WLiu M(2023)A method to recommend cloud manufacturing service based on the spectral clustering and improved Slope one algorithmJournal of Cloud Computing: Advances, Systems and Applications10.1186/s13677-023-00489-512:1Online publication date: 3-Aug-2023
https://dl.acm.org/doi/10.1186/s13677-023-00489-5
Chen HSun HCheng MYan W(2021)A Recommendation Approach for Rating Prediction Based on User Interest and Trust ValueComputational Intelligence and Neuroscience10.1155/2021/66779202021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/6677920
Pérez-Núñez PLuaces OBahamonde ADíez J(2020)Improving recommender systems by encoding items and user profiles considering the order in their consumption historyProgress in Artificial Intelligence10.1007/s13748-019-00199-79:1(67-75)Online publication date: 1-Mar-2020
https://dl.acm.org/doi/10.1007/s13748-019-00199-7
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A recommender system based on historical usage data for web service discovery
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
  2. World Wide Web

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Published In

cover image Service Oriented Computing and Applications

Service Oriented Computing and Applications Volume 6, Issue 1

March 2012

76 pages

ISSN:1863-2386

Issue’s Table of Contents

Copyright © Copyright © 2012 Springer-Verlag London Limited.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 March 2012

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Cited By

Hu QQi HHuang WLiu M(2023)A method to recommend cloud manufacturing service based on the spectral clustering and improved Slope one algorithmJournal of Cloud Computing: Advances, Systems and Applications10.1186/s13677-023-00489-512:1Online publication date: 3-Aug-2023
https://dl.acm.org/doi/10.1186/s13677-023-00489-5
Chen HSun HCheng MYan W(2021)A Recommendation Approach for Rating Prediction Based on User Interest and Trust ValueComputational Intelligence and Neuroscience10.1155/2021/66779202021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/6677920
Pérez-Núñez PLuaces OBahamonde ADíez J(2020)Improving recommender systems by encoding items and user profiles considering the order in their consumption historyProgress in Artificial Intelligence10.1007/s13748-019-00199-79:1(67-75)Online publication date: 1-Mar-2020
https://dl.acm.org/doi/10.1007/s13748-019-00199-7
Criado JBoubeta-Puig JMena MLlopis JOrtiz GIribarne L(2020)Towards the Integration of Web of Things Applications Based on Service DiscoveryCurrent Trends in Web Engineering10.1007/978-3-030-65665-2_3(24-29)Online publication date: 9-Jun-2020
https://dl.acm.org/doi/10.1007/978-3-030-65665-2_3
Kala AZayani CAmous IAbdelghani WSdes F(2018)Social collaborative service recommendation approach based on users trust and domain-specific expertiseFuture Generation Computer Systems10.1016/j.future.2017.05.03680:C(355-367)Online publication date: 1-Mar-2018
https://dl.acm.org/doi/10.1016/j.future.2017.05.036
Riyana SNatwichai J(2018)Privacy preservation for recommendation databasesService Oriented Computing and Applications10.1007/s11761-018-0248-y12:3-4(259-273)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1007/s11761-018-0248-y
Yanes NBen Sassi SHajjami Ben Ghezala H(2017)Ontology-based recommender system for COTS componentsJournal of Systems and Software10.1016/j.jss.2017.07.031132:C(283-297)Online publication date: 1-Oct-2017
https://dl.acm.org/doi/10.1016/j.jss.2017.07.031
Rapti EKarageorgos AHoustis CHoustis E(2017)Decentralized service discovery and selection in Internet of Things applications based on artificial potential fieldsService Oriented Computing and Applications10.1007/s11761-016-0198-111:1(75-86)Online publication date: 1-Mar-2017
https://dl.acm.org/doi/10.1007/s11761-016-0198-1
Mahmoud CBettahar FAzaiez IGargouri F(2016)OWLS-LOInternational Journal of Metadata, Semantics and Ontologies10.1504/IJMSO.2016.07811111:1(61-70)Online publication date: 1-Jan-2016
https://dl.acm.org/doi/10.1504/IJMSO.2016.078111
Jannach DJugovac MLerche L(2016)Supporting the Design of Machine Learning Workflows with a Recommendation SystemACM Transactions on Interactive Intelligent Systems10.1145/28520826:1(1-35)Online publication date: 22-Feb-2016
https://dl.acm.org/doi/10.1145/2852082
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