PROJECT TITLE :
Extraction Algorithm of English Text Summarization for English Teaching - 2018
In order to improve the power of sharing and scheduling capability of English teaching resources, an improved algorithm for English text summarization is proposed primarily based on Association semantic rules. The relative options are mined among English text phrases and sentences, the semantic relevance analysis and have extraction of keywords in English abstract are realized, the association rules differentiation for English text summarization is obtained based on information theory, connected semantic rules data in English Teaching Texts is mined. Text similarity feature is taken as the maximum difference component of two semantic association rule vectors, and combining semantic similarity info, the correct extraction of English text Abstract is realized. The simulation results show that the tactic can extract the text summarization accurately, it's better convergence and precision performance in the extraction process.
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