A Query Based Summarization Service from Multiple News Sources
It can be time consuming to search Internet news, due to multiple sources reporting repetitive information. Given a query and a set of relevant text articles, query focused multi document summarization (QMDS) aims to generate a fluent, well organized, and compact summary that answers the query. While QMDS helps to summarize search results, most top performing systems for this purpose remain largely extractive. Extractive summarization extracts a group of sentences and concatenates them. In this paper, we propose a summarization service based on abstractive QMDS using multi sentence compression (MSC) Our proposed service generates a novel summary representing the gist of the content of the source document(s) Experiments using popular summarization benchmark datasets demonstrate the effectiveness of the proposed service.
2016 IEEE International Conference on Services Computing (SCC)