[1]CHANG Liang,ZHANG Weitao,GU Tianlong,et al.Review of recommendation systems based on knowledge graph[J].CAAI Transactions on Intelligent Systems,2019,14(2):207-216.[doi:10.11992/tis.201805001]
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Review of recommendation systems based on knowledge graph
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
14
Number of periods:
2019 2
Page number:
207-216
Column:
综述
Public date:
2019-03-05
- Title:
- Review of recommendation systems based on knowledge graph
- Keywords:
- knowledge graph; recommendation system; ontology; linked open data; graph embedding; network representation learning; similarity; prediction score
- CLC:
- TP301
- DOI:
- 10.11992/tis.201805001
- Abstract:
- In current research on recommendation systems, the provision of personalized recommendations to users and the improvement of the accuracy and user satisfaction of recommendations are main concerns. The emergence of knowledge graphs provides a new way to improve recommendation systems. The applications of knowledge graphs to recommendation systems in recent years are summarized in this paper, and the current status of the research is investigated in detail from three aspects:ontology-based recommendation generation, recommendation generation based on linked open data, and recommendation generation based on graph embedding. On this basis, this paper proposes the general framework of recommendation systems based on knowledge graph, analyzes the key technologies involved, discusses the existing key issues and difficulties, and indicates the further research work to be carried out.
- References:
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Last Update:
2019-04-25