Recommender System Based on Random Walks and Text Retrieval Approaches
نویسندگان
چکیده
This paper presents the approaches IRIT developed for the VLNetChallenge regarding recommender systems in the context of video lectures. The first task aims at recommending newly acquired lectures after viewing an “old” lecture. We use random walk algorithms based on a graph composed of author, category, event, and lecture nodes and associated relationships. The second task aims at recommending 10 lectures from three lectures extracted from a sequence of lectures. We use the categories associated to lectures in addition to the lecture pairs (lectures viewed in a same session).
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