An approach of conceptual knowledge broaden based E-Commerce Recommendation

E-Commerce recommendation helps consumers find the products and services that they want. Many challenging research problems in E-Commerce remain. Most research use syntactic matching techniques while they miss a lot of useful knowledge during the recommendation process. An approach on conceptual broaden knowledge based E-Commerce Recommendation is proposed in this paper that overcomes these drawbacks. The word acquiring algorithm is applied to collect the recommender word and some typically combinations, based on the Information Entropy. Meanwhile the general dictionary and the special dictionaries are constructed, and inquiring broaden algorithm is used to combine with concept knowledge. Experiments show that the proposed approach is effective.