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Similarity metric is the core of k-nearest neighbor collaborative filtering in recommender systems. However, traditional metrics measure the similarity among neighbors only in either direction or distance. In this paper, we propose a triangle similarity metric and two kinds of hybrid ones based on it for dynamic interaction recommendation. First, the triangle similarity metric combines both direction...
Recommender systems represent user preferences for the purpose of suggesting items to select or examine. In petroleum drilling safety check, there are many items (e.g. tool misused and warning signs ignored) to be checked during one day. However, existing recommender systems seldom apply time series and interaction methods for the issue. In this paper, we propose a recommender system with two techniques...
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