On-line Summarization of Time-series Documents using a Graph-based Algorithm

As enormous amount of electronic documents on the Web have been increasing, the necessity of automatic summarization has also been increasing to help people grasp the essential points of the documents. Many summarization techniques dealing with single document and multi-documents have been studied. However, due to the increase of the documents which report the change of topics along a timeline, called time-series documents, in recent years, a summarization technique which generates a summary of timeseries documents, called timeline summarization, has been actively studied as an area of automatic summarization. There are different difficulties in summarizing time-series documents from other type of automatic summarization. The basic approach for timeline summarization is to extract sentences which describe major events in object documents in chronological order to generate a timeline summary. However, unlike the prior studies of timeline summarization, we particularly focus on online summarization of time-series documents and propose an on-line graph-based timeline summarization method. With our proposed method, a summary of time-series documents can be generated at any point of time when it is required. We conduct experiments to investigate the ability of our proposed method, evaluate the results with ROUGEmetrics, and show our proposed method produces a better summary compared to other representative summarization methods.