Research of personalized knowledge search for food safety system

doi:10.3969/j.issn.1000-5641.2017.05.011

Abstract

Abstract: In the era of big data, knowledge discovery from the mass of data is an important research problem, especially for the user's customized knowledge. In this paper, an integrated search system aiming at personalized re-ranking of food safety knowledge system, PROSK for short, is designed and implemented. Firstly, using the existing search engines, the meta-search engine technique is employed for integrating the results of multiple search engines; then according to the results of the users' click through and the ontology of food safety domain, ranking-based learning algorithm is applied to sort search results adaptively according to the preference profiles. The system integrates the agricultural information from multi-engineers and ranks the query results adaptively and intelligently. This study proposes a feasible solution for ranking of information and knowledge of food safety from multi-engineers adaptively.

Key words: food safety search, personalized ranking, search engine integration, domain ontology

CLC Number:

TP391

YUAN Pei-sen, REN Wu-bei, REN Shou-gang, ZHU Shu-xin, XU Huan-liang. Research of personalized knowledge search for food safety system[J]. Journal of East China Normal University(Natural Sc, 2017, 2017(5): 117-124,137.

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