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A personalized recommendation for web api discovery in social web of things
Joint Authors
Kazar, Okba
Meissa, Marwah
Benharzallah, Saber
Kahloul, Laid
Source
The International Arab Journal of Information Technology
Issue
Vol. 18, Issue 3A (s) (31 May. 2021), pp.438-445, 8 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2021-05-31
Country of Publication
Jordan
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
With the explosive growth of Web of Things (WoT) and social web, it is becoming hard for device owners and users to find suitable web Application Programming Interface (API) that meet their needs among a large amount of web APIs.
Social aware and collaborative filtering-based recommender systems are widely applied to recommend personalized web APIs to users and to face the problem of information overload.
However, most of the current solutions suffer from the dilemma of accuracy diversity where the prediction accuracy gains are typically accompanied by losses in the diversity of the recommended APIs due to the influence of popularity factor on the final score of APIs (e.g., high rated or high-invoked APIs).
To address this problem, the purpose of this paper is developing an improved recommendation model called (Personalized Web API Recommendation) PWR, which enables to discover APIs and provide personalized suggestions for users without sacrificing the recommendation accuracy.
To validate the performance of our model, seven variant algorithms of different approaches (popularity-based, user based and item-based) are compared using Movie Lens 20M dataset.
The experiments show that our model improves the recommendation accuracy by 12% increase with the highest score among compared methods.
Additionally, it outperforms the compared models in diversity over all lengths of recommendation lists.
It is envisaged that the proposed model is useful to accurately recommend personalized web API for users.
American Psychological Association (APA)
Meissa, Marwah& Benharzallah, Saber& Kahloul, Laid& Kazar, Okba. 2021. A personalized recommendation for web api discovery in social web of things. The International Arab Journal of Information Technology،Vol. 18, no. 3A (s), pp.438-445.
https://search.emarefa.net/detail/BIM-1439916
Modern Language Association (MLA)
Meissa, Marwah…[et al.]. A personalized recommendation for web api discovery in social web of things. The International Arab Journal of Information Technology Vol. 18, no. 3A (Special issue) (2021), pp.438-445.
https://search.emarefa.net/detail/BIM-1439916
American Medical Association (AMA)
Meissa, Marwah& Benharzallah, Saber& Kahloul, Laid& Kazar, Okba. A personalized recommendation for web api discovery in social web of things. The International Arab Journal of Information Technology. 2021. Vol. 18, no. 3A (s), pp.438-445.
https://search.emarefa.net/detail/BIM-1439916
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 443-444
Record ID
BIM-1439916