In order to solve the problem of ignoring items’ attributes in single criteria collaborative filtering recommendation algorithm, a collaborative filtering recommendation algorithm based on multi-criteria decision making was proposed. Multi-criteria decision making was used during the computing of users’ similarity in the algorithm. By averaging all the similarities of sub evaluation with their weight, the algorithm chose the nearest neighbors. Finally, the algorithm used several nearest neighbors to get the recommendation results. Experiments show that the algorithm can find the nearest neighbors more similar after detailing evaluation, and make better predictions for the target users.
The paper proposes an ontology construction approach that combines Fuzzy Formal Concept Analysis, Wikipedia and WordNet in a process that constructs multiple concept lattices for sub-domains. Those sub-domains are divided from the target domain. The multiple concept lattices approach can mine concepts and determine relations between concepts automatically, and construct domain ontology accordingly. This approach is suitable for the large domain or complex domain which contains obvious sub-domains.
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