Extractive text summarization is to find the important sentences from texts and concatenates these sentences as a summary. However, sentences selected according to ranking rules are usually not coherent. Is a larger language unit such as a group of sentences or a paragraph more appropriate to be selected for summarization? This paper is to answer this question. Investigating the summarization algorithm based on ranking semantic link networks of texts, we find the following three results: 1) comparing with the summaries composed by sentences, the summaries composed by larger language units have similar ROUGE scores but have better readability; 2) using a group of sentences is more effective than using sentence and paragraph; and, 3) the quality of summaries composed by group becomes better when the average length of the source texts increases.
|Name||2018 14th International Conference on Semantics, Knowledge and Grids (SKG)|
|Conference||2018 14th International Conference on Semantics, Knowledge and Grids (SKG)|
|Period||12/09/18 → 14/09/18|
- semantic link network
- text summarization