Personalized Knowledge Recommendation Based on Knowledge Graph in Petroleum Exploration and Development

Abstract

Firstly, this paper designs the process of personalized recommendation method based on knowledge graph, and constructs user interest model. Second, the traditional personalized recommendation algorithms are studied and their advantages and disadvantages are analyzed. Finally, this paper focuses on the combination of knowledge graph and collaborative filtering recommendation algorithm. They are effective to solve the problem where [Formula: see text] value is difficult to be determined in the clustering process of traditional collaborative filtering recommendation algorithm as well as data sparsity and cold start, utilizing the ample semantic relation in knowledge graph. If we use RDF data, which is distributed by the E and P (Exploration and Development) database based on the petroleum E and P, to verify the validity of the algorithm, the result shows that collaborative filtering algorithm based on knowledge graph can build the users’ potential intentions by knowledge graph. It is enlightening to query the information of users. In this way, it expands the mind of users to accomplish the goal of recommendation. In this paper, a collaborative filtering algorithm based on domain knowledge atlas is proposed. By using knowledge graph to effectively classify and describe domain knowledge, the problems are solved including clustering and the cold start in traditional collaborative filtering recommendation algorithm. The better recommendation effect has been achieved.

Retracted: QGMS: A query growth model for personalization and diversification of semantic search based on differential ontology semantics using artificial intelligence

“…The model is based on principled R e t r a c t e d language modeling strategies on a large knowledge graph to yield queries that are informative and complete. Huang et al 4 have proposed a knowledge recommendation approach based on a knowledge graph specific to the petroleum domain. A collaborative filtering strategy over an atlas of domain knowledge for solving the cold start recommendation and improving personalization in the recommendation.…”

Civil Aviation Travel Question and Answer Method Using Knowledge Graphs and Deep Learning

“…Chen et al [27] proposed a forest fire prediction method based on knowledge graphs and representation learning. Huang et al [28] constructed methods and proposed applications of knowledge graphs in oil exploration and development. Gupta et al [29] designed a knowledge graph for missiles.…”