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The collaborative filtering recommendation algorithm of power big data based on knowledge correlation. (Chinese. English summary) Zbl 1413.68174

Summary: Most collaborative filtering recommendation algorithms are based on the object similarity without taking knowledge correlation in grid domain into account, which leads to inaccurate ranking result. Aiming at this problem, this paper adopts the structure of knowledge tree to organize grid domain knowledge and mines the correlation between different knowledge items. The experiment results show that the algorithm can effectively solve the problems of the low correlation degree of recommendation results and significantly improve the quality of the recommendation results and the recommendation efficiency.

MSC:

68U35 Computing methodologies for information systems (hypertext navigation, interfaces, decision support, etc.)
68P10 Searching and sorting
68T35 Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence
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