Semantic Representation & Analysis (SRA) and potential applications

[视频介绍]
简介:Semantic Representation Analysis (SRA) is a general framework for vector-based semantic analysis. Within this framework, semantics of natural language are represented in the form of Induced Semantic Structure (ISS). SRA has applications in information retrieval (IR), text analysis, and intelligent tutoring systems (ITS). In this lecture, I will 1) introduce a mathematical model of SRA; 2) introduce and demonstrate a method that generates individualized domain-specific context sensitive semantic representation; 3) introduce and demonstrate learner’s characteristics curves (LCC) as local student’s model and its application in intelligent tutoring systems.
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视频介绍

讲师:Xiangen Hu

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课程简介:Semantic Representation Analysis (SRA) is a general framework for vector-based semantic analysis. Within this framework, semantics of natural language are represented in the form of Induced Semantic Structure (ISS). SRA has applications in information retrieval (IR), text analysis, and intelligent tutoring systems (ITS). In this lecture, I will 1) introduce a mathematical model of SRA; 2) introduce and demonstrate a method that generates individualized domain-specific context sensitive semantic representation; 3) introduce and demonstrate learner’s characteristics curves (LCC) as local student’s model and its application in intelligent tutoring systems.