Automatic text summarization based on thematic word weight and sentence features

作者：Jiang, Chang-Jin^*; Peng, Hong; Chen, Jian-Chao; Ma, Qian-Li

来源：Journal of South China University of Technology(Natural Science Edition), 2010, 38(7): 50-55.

DOI：10.3969/j.issn.1000-565X.2010.07.009

• Automatic text summarization
• Combined word
• Sentence features
• Thematic words
• Weight computing

In order to generate high-quality automatic text summarization, a formula based on the combined word recognition algorithm is presented to compute the weight of words in a text, with the word frequency, part of speech, word position and word length being considered. By using the proposed formula, a thematic word/phrase is assigned great weight, a sentence is weighted according to its content and position, the cue words in it and the user's preference, and the final summarization is generated by fully considering the similarity of candidate sentences, thus avoiding the information redundance. Moreover, the evaluation approach based on the accuracy and the recall of summarization is improved to increase the computing precision of summarization to the word level instead of the sentence level. Experimental results show that the proposed algorithm generates high-quality summaries, with an average precision of 77.1%.

• 出版日期2010-7
• 单位华南理工大学