Entity Relationship Explanation via Conceptualization  

作　　者：谢晨昊 梁家卿 肖仰华 HWANG Seung-won XIE Chenhao;LIANG Jiaqing;XIAO Yanghua;HWANG Seung-won(School of Computer Science,Fudan University,Shanghai 200433,China;Department of Computer Science and Engineering,Seoul National University,Seoul 08826,Republic of Korea)

机构地区：[1]School of Computer Science,Fudan University,Shanghai 200433,China [2]Department of Computer Science and Engineering,Seoul National University,Seoul 08826,Republic of Korea

出　　处：《Journal of Shanghai Jiaotong university(Science)》2023年第6期695-702,共8页上海交通大学学报（英文版）

基　　金：the Shanghai Science and Technology Innovation Action Plan(No.19511120400);the National Key Research and Development Project(No.2020AAA0109302);the Shanghai Municipal Science and Technology Major Project(No.2021SHZDZX0103)。

摘　　要：Finding an attribute to explain the relationships between a given pair of entities is valuable in many applications.However,many direct solutions fail,owing to its low precision caused by heavy dependence on text and low recall by evidence scarcity.Thus,we propose a generalization-and-inference framework and implement it to build a system:entity-relationship finder(ERF).Our main idea is conceptualizing entity pairs into proper concept pairs,as intermediate random variables to form the explanation.Although entity conceptualization has been studied,it has new challenges of collective optimization for multiple relationship instances,joint optimization for both entities,and aggregation of diluted observations into the head concepts defining the relationship.We propose conceptualization solutions and validate them as well as the framework with extensive experiments.

关 键 词：relation explanation knowledge base entity-relationship finder(ERF) probabilistic generative model 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]