Integrating geographical and functional relevance to implicit data for web service recommendation

Khavee Agustus Botangen*, Jian Yu, Sira Yongchareon, Liang Huai Yang, Quan Z. Sheng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

5 Citations (Scopus)


Designing efficient and effective Web service recommendation, primarily based on usage feedback, has become an important task to support the prevalent consumption of services. In the mashup-API invocation scenario, the most available feedback is the implicit invocation data, i.e., the binary data indicating whether or not a mashup has invoked an API. Hence, various efforts are exploiting potential impact factors to augment the implicit invocation data with the aim to improve service recommendation performance. One significant factor affecting the context of Web service invocations is geographical location, however, it has been given less attention in the implicit-based service recommendation. In this paper, we propose a recommendation approach that derives a contextual preference score from geographical location information and functionality descriptions. The preference score complements the mashup-API invocation data for our implicit-tailored matrix factorization recommendation model. Evaluation results show that augmenting the implicit data with geographical location information and functionality description significantly increases the precision of API recommendation for mashup services.

Original languageEnglish
Title of host publicationService-Oriented Computing
Subtitle of host publication17th International Conference, ICSOC 2019, Proceedings
EditorsSami Yangui, Ismael Bouassida Rodriguez, Khalil Drira, Zahir Tari
Place of PublicationSwitzerland
Number of pages5
ISBN (Electronic)9783030337025
ISBN (Print)9783030337018
Publication statusPublished - 2019
Event17th International Conference on Service-Oriented Computing, ICSOC 2019 - Toulouse, France
Duration: 28 Oct 201931 Oct 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11895 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference17th International Conference on Service-Oriented Computing, ICSOC 2019


  • Implicit feedback
  • Location
  • Matrix factorization
  • Recommendation
  • Topic model


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