Simplifying mashup component selection with a combined similarity- and social-based technique
Proceedings of the 5th International Workshop on Web APIs and Service Mashups
Socially-Enriched semantic mashup of web APIs
ICSOC'12 Proceedings of the 10th international conference on Service-Oriented Computing
Personalised graph-based selection of web APIs
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
A classification of web API selection solutions over the linked web
Proceedings of the 2nd International Workshop on Semantic Search over the Web
Towards a folksonomy of web APIs
Proceedings of the 3rd International Workshop on Semantic Search Over the Web
A framework for guided search of mashup components
Proceedings of the 3rd International Workshop on Semantic Search Over the Web
Advanced Web API search patterns adding collective knowledge to public repository facets
Proceedings of International Conference on Information Integration and Web-based Applications & Services
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A common problem that mashup developers face is the discovery of APIs that suit their needs. This primary task becomes harder, tedious and time-consuming with the proliferation of new APIs. As humans, we learn by example, following community previous decisions when creating mashups. Most techniques do not consider at all reusing this social information. In this paper, we propose to combine current discovery techniques (exploration) with social information (exploitation). Our preliminary results show that by considering the reciprocal influence of both sources, the discovery process reveals APIs that would remain with low rank because the preferential attachment (popularity) and/or the lack of better descriptions (discovery techniques). We present a case study focusing on a public Web-based API registry.