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The rapid development of online services and information overload has inspired the fast development of recommender systems, among which collaborative filtering algorithms and model-based recommendation approaches are wildly exploited. For instance, matrix factorization (MF) demonstrated successful achievements and advantages in assisting internet users in finding interested information. These existing...
Nowadays, many social tourism platforms, such as tripadvisor.com and lvping.com, provide tourists opportunities to share their experiences on tourism destinations, services and sites. The increasing number of these available opinions makes potential travelers impossible easily discovering helpful information from an immense number of lengthy travelogues. Therefore, it is vitally important to develop...
Web services, as loosely-coupled software systems, are increasingly being published to the web and there are a large number of services with similar functions. Therefore, service users compare the non-functional properties of services, e.g., Quality of Service (QoS), when they make service selection. This paper aims at generating a more comprehensive web service recommendation to users with a novel...
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