In order to improve the ability of sharing and scheduling capability of English teaching resources, an improved algorithm for English text summarization is proposed based on Association semantic rules. The relative fe...In order to improve the ability of sharing and scheduling capability of English teaching resources, an improved algorithm for English text summarization is proposed based on Association semantic rules. The relative features are mined among English text phrases and sentences, the semantic relevance analysis and feature extraction of keywords in English abstract are realized, the association rules differentiation for English text summarization is obtained based on information theory, related semantic roles information 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 information, the accurate extraction of English text Abstract is realized. The simulation results show that the method can extract the text summarization accurately, it has better convergence and precision performance in the extraction process.展开更多
文摘In order to improve the ability of sharing and scheduling capability of English teaching resources, an improved algorithm for English text summarization is proposed based on Association semantic rules. The relative features are mined among English text phrases and sentences, the semantic relevance analysis and feature extraction of keywords in English abstract are realized, the association rules differentiation for English text summarization is obtained based on information theory, related semantic roles information 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 information, the accurate extraction of English text Abstract is realized. The simulation results show that the method can extract the text summarization accurately, it has better convergence and precision performance in the extraction process.