A comparison of recommender systems for mashup composition

Author

Cremonesi, Paolo ; Picozzi, Matteo ; Matera, Maristella

Author_Institution

DEI, Politec. di Milano, Milano, Italy

fYear

2012

fDate

4-4 June 2012

Firstpage

54

Lastpage

58

Abstract

Web mashups are a new generation of applications created by composing contents and functions available through Web services and APIs. A central activity in mashup development is the retrieval and selection of components to be included in the composition. The adoption of recommender systems can alleviate some of the difficulties arising in this activity. Based on the results of an empirical study, this paper tries to shed light on the application of recommender systems to the mashup composition domain, and discusses the performance of different recommendation systems when applied to a very large collection of mashups and mashup components.

Keywords

Web services; application program interfaces; information retrieval; recommender systems; API; Web mashups; Web services; component retrieval; component selection; mashup composition domain; mashup development; recommendation systems; recommender systems; Accuracy; Collaboration; Mashups; Matrix decomposition; Measurement; Prediction algorithms; Recommender systems; APIs; Recommender systems; Web mashups;

fLanguage

English

Publisher

ieee

Conference_Titel

Recommendation Systems for Software Engineering (RSSE), 2012 Third International Workshop on

Conference_Location

Zurich

Print_ISBN

978-1-4673-1758-0

Type

conf

DOI

10.1109/RSSE.2012.6233411

Filename

6233411