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meet users’ personalized requirements. In this paper, we propose a Keyword-Aware Service Recommendation method, named KASR, to address the above challenges. It aims at presenting a personalized service recommendation list and recommending the most appropriate services to the users effectively. Specifically
on Map-Reduce, named PASR, is proposed in this paper. It aims at presenting a personalized ranking list and recommending the most appropriate services to the users from big data environment. In this method, keywords are used to indicate users' preferences, and a user based Collaborative Filtering algorithm is adopted to
This paper's research work mainly pays attention to the requirement consistency validation. In order to solve the consistency evaluation and multi-branch selection problem during requirement validation process, this paper proposes a kind of requirement measurement method. At first, this paper proposes a keywords
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.