A Group Recommender System based on Neural Network Collaborative Filtering Algorithm
| Autor: | Rui-zhe Zhang, 張睿哲 |
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| Rok vydání: | 2011 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 99 In the research field of Recommender System, the personalized recommender system has always been regarded as the main trend. The main operation is to record the pattern of personal behavior in the system and then the system will recommend users which program to use according to users’ preferences. However, consumer behaviors and recreational activities are not both formed by one single individual, many of which will be made by groups. For example, when relatives and friends get together to go to see movies, go travelling or having meals, the single user recommender system can’t achieve the application targets for above situations. In the past, the group recommender system intended to combine users’ preference on the same aspect to achieve different variety of measurement. However, this approach ignores individual member’s characteristics and the pattern of how each member interacts with others; such that this sort of measurement can’t truly reflect real interest on the same issue. The main target of our research is to develop a group recommender system based on neural network training algorithms. We proposed to train and get weights in the neural network and to simulate phenomena made by the interaction among groups by measuring the same issue made by each individual or the whole group. Finally, we evaluate our approach experimentally and compare it in different parameter of network. The experimental result shows that we can achieve the function of being user-friendly by algorithm in the group recommender system that can’t be achieve by algorithm in the personalized recommender system. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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