Optimization of Session Topic Backtracking Method Based on Interactive Text

Conversation topic tracing refers to the use of conversation topics to trace back the subjects and related information associated with the topic. This article first focuses on the need for topic backtracking and constructs a conversation topic backtracking model. Secondly, optimize the feature selec...

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Bibliographic Details
Published in2024 7th International Conference on Advanced Algorithms and Control Engineering (ICAACE) pp. 262 - 265
Main Authors Chen, Ding, Song, Ziang, Song, Zhenyu, Xu, Yatao
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2024
Subjects
Backtracking
Conversation topic
Dictionaries
Feature extraction
Interactive text
Lridf algorithm
Oral communication
Refining
Semantics
Technological innovation
Topic backtracking
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DOI10.1109/ICAACE61206.2024.10549663

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Summary:Conversation topic tracing refers to the use of conversation topics to trace back the subjects and related information associated with the topic. This article first focuses on the need for topic backtracking and constructs a conversation topic backtracking model. Secondly, optimize the feature selection algorithm TFIDF and propose an improved algorithm LRIDF. Thirdly, applying the above research results, propose an optimized interactive text conversation topic backtracking method. Empirical analysis shows that this method can effectively improve the performance of conversation topic backtracking.
DOI:10.1109/ICAACE61206.2024.10549663