Research on Recommender Systems for Further Education


Recently, many researches have been done on multiple types of recommender systems, including job recommending, movie recommending, commodity recommending etc. However, as a kind of recommender system needed by many students, further education-oriented recommender systems are rarely mentioned. In this paper, we propose a preliminary recommender system based on profile comparison applied in further education, which can recommend professors to students. In order to compare the profiles of student and professors, we proposed a distance function using word2vec and doc2vec. Moreover, regarding the amount of history data collected during operation, we separate the model into two stages. In the two stages, different methods of giving recommendations are applied.

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