zuoxin
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- Associate professor
- Supervisor of Master's Candidates
- Name (Pinyin):zuoxin
- E-Mail:
- School/Department:长春工业大学外国语学院
- Administrative Position:教师
- Education Level:Postgraduate (Master's Degree)
- Degree:Master's degree
- Professional Title:Associate professor
- Status:Employed
- Alma Mater:东北师范大学外国语学院
- Teacher College:外国语学院
- Discipline:Linguistics and Applied Linguistics in Foreign Languages
Contact Information
- Email：
- Paper Publications
（ISTP)Learning Causal Semantic Representation from Information Extraction
Release time:2022-08-24 Hits:
- Affiliation of Author(s):外国语学院
- Teaching and Research Group:第一英语教研室
- Journal:2009 International Symposium on Intelligent Ubiquitous Computing and Education
- Funded by:省教育厅社科项目
- Key Words:causal semantic representation; logical rules; generalized information theory
- Abstract:For reasoning with uncertain knowledge causal semantic analysis is proposed to construct logical rules, which are extracted from decision tree induction and bayes inference based on generalized information theory. These rules can represent multi-level semantic knowledge of the relationship between the data and information implicated. Empirical studies on a set of natural domains show that the semantic completeness of generalized information theory has clear advantage in representing semantic knowledge from different levels.
- Co-author:王利民,zhoushuang
- First Author:zuoxin
- Indexed by:Essay collection
- Page Number:2
- Translation or Not:no
- Date of Publication:2009-06-16