Leveraging online behaviors for interpretable knowledge-aware patent recommendation

doi:10.1108/INTR-08-2020-0473

	Leveraging online behaviors for interpretable knowledge-aware patent recommendation
	Du, Wei 1; Yan, Qiang 2; Zhang, Wenping 1; Ma, Jian 3
	2021-06-11
发表期刊	INTERNET RESEARCH
ISSN	1066-2243
页码	20
摘要	Purpose Patent trade recommendations necessitate recommendation interpretability in addition to recommendation accuracy because of patent transaction risks and the technological complexity of patents. This study designs an interpretable knowledge-aware patent recommendation model (IKPRM) for patent trading. IKPRM first creates a patent knowledge graph (PKG) for patent trade recommendations and then leverages paths in the PKG to achieve recommendation interpretability. Design/methodology/approach First, we construct a PKG to integrate online company behaviors and patent information using natural language processing techniques. Second, a bidirectional long short-term memory network (BiLSTM) is utilized with an attention mechanism to establish the connecting paths of a company - patent pair in PKG. Finally, the prediction score of a company - patent pair is calculated by assigning different weights to their connecting paths. The semantic relationships in connecting paths help explain why a candidate patent is recommended. Findings Experiments on a real dataset from a patent trading platform verify that IKPRM significantly outperforms baseline methods in terms of hit ratio and normalized discounted cumulative gain (nDCG). The analysis of an online user study verified the interpretability of our recommendations. Originality/value A meta-path-based recommendation can achieve certain explainability but suffers from low flexibility when reasoning on heterogeneous information. To bridge this gap, we propose the IKPRM to explain the full paths in the knowledge graph. IKPRM demonstrates good performance and transparency and is a solid foundation for integrating interpretable artificial intelligence into complex tasks such as intelligent recommendations.
关键词	Interpretable knowledge-aware recommendation Patent recommendation Online behaviors
DOI	10.1108/INTR-08-2020-0473
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[71901208] ; National Natural Science Foundation of China[71771212] ; National Natural Science Foundation of China[U1711262] ; National Natural Science Foundation of China[71801217] ; Humanities and Social Sciences Foundation of the Ministry of Education[18YJC630025] ; Key Projects of Philosophy and Social Sciences Research of Chinese Ministry of Education[19JZD021] ; Ministry of Education, Science and Technology Development Center[2019J01010]
WOS研究方向	Business & Economics ; Computer Science ; Telecommunications
WOS类目	Business ; Computer Science, Information Systems ; Telecommunications
WOS记录号	WOS:000660627500001
出版者	EMERALD GROUP PUBLISHING LTD
引用统计	被引频次：7[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/17669
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhang, Wenping
作者单位	1.Renmin Univ China, Sch Informat, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 3.City Univ Hong Kong, Coll Business, Informat Syst, Hong Kong, Peoples R China
推荐引用方式 GB/T 7714	Du, Wei,Yan, Qiang,Zhang, Wenping,et al. Leveraging online behaviors for interpretable knowledge-aware patent recommendation[J]. INTERNET RESEARCH,2021:20.
APA	Du, Wei,Yan, Qiang,Zhang, Wenping,&Ma, Jian.(2021).Leveraging online behaviors for interpretable knowledge-aware patent recommendation.INTERNET RESEARCH,20.
MLA	Du, Wei,et al."Leveraging online behaviors for interpretable knowledge-aware patent recommendation".INTERNET RESEARCH (2021):20.