@inproceedings {conf/services/MaaradjiHSV11,
	title = {Social Web Mashups Full Completion via Frequent Sequence Mining},
	booktitle = {SERVICES},
	year = {2011},
	pages = {9-16},
	publisher = {IEEE Computer Society},
	organization = {IEEE Computer Society},
	abstract = {<p>In this paper we address the problem of WebMashups full completion which consists of predicting themost suitable set of (combined) services that successfully meetthe goals of an end-user Mashup, given the current service(or composition of services) initially supplied. We model fullcompletion as a frequent sequence mining problem and weshow how existing algorithms can be applied in this context.To overcome some limitations of the frequent sequence miningalgorithms, e.g., efficiency and recommendation granularity,we propose FESMA, a new and efficient algorithm for computingfrequent sequences of services and recommending completions.FESMA also integrates a social dimension, extractedfrom the transformation of user ? service interactions intouser ? user interactions, building an implicit graph thathelps to better predict completions of services in a fashiontailored to individual users. Evaluations show that FESMAis more efficient outperforming the existing algorithms evenwith the consideration of the social dimension. Our proposalhas been implemented in a prototype, SoCo, developed at BellLabs.</p>
},
	keywords = {Mashups, Sequence mining, Social networks, Web services},
	isbn = {978-1-4577-0879-4},
	author = {Maaradji, Abderrahmane and Hacid, Hakim and Skraba, Ryan and Athena Vakali}
}