| Autor: |
LIU Zhonghui, ZOU Lu, YANG Mei, MIN Fan |
| Jazyk: |
čínština |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Jisuanji kexue yu tansuo, Vol 14, Iss 4, Pp 703-711 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
1673-9418 |
| DOI: |
10.3778/j.issn.1673-9418.1905012 |
| Popis: |
Formal concept analysis is a data analysis method for formal context and has been introduced into the field of recommender systems. As an effective tool for formal concept analysis, concept lattice is difficult to cope with large-scale data in e-commerce because of its low construction efficiency. To solve this problem, this paper proposes a group recommendation method based on heuristic concept construction. Firstly, based on user??s common scoring items, a heuristic information is defined to speed up construction of concept. At the same time, using the intension constraint, a concept with largest area is constructed to aggregate more similar users. Then, on the concept set covering all users, group users in the concept are recommended by items popularity of the group. In the sampled data sets and MovieLens, the proposed method is compared to two different recommended methods. The experi-mental results show that the method can quickly generate a set of concepts to meet the recommendation require-ments under large-scale data. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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