Solving Multi-Document Summarization as an Orienteering Problem
AbstractWith advances in information technology, people face the problem of dealing with tremendous amounts of information and need ways to save time and effort by summarizing the most important and relevant information. Thus, automatic text summarization has become necessary to reduce the information overload. This article proposes a novel extractive graph-based approach to solve the multi-document summarization (MDS) problem. To optimize the coverage of information in the output summary, the problem is formulated as an orienteering problem and heuristically solved by an ant colony system algorithm. The performance of the implemented system (MDS-OP) was evaluated on DUC 2004 (Task 2) and MultiLing 2015 (MMS task) benchmark corpora using several ROUGE metrics, as well as other methods. Its comparison with the performances of 26 systems shows that MDS-OP achieved the best F-measure scores on both tasks in terms of ROUGE-1 and ROUGE-L (DUC 2004), ROUGE-SU4, and three other evaluation methods (MultiLing 2015). Overall, MDS-OP ranked among the best 3 systems. View Full-Text
Share & Cite This Article
Al-Saleh, A.; Menai, M.E.B. Solving Multi-Document Summarization as an Orienteering Problem. Algorithms 2018, 11, 96.
Al-Saleh A, Menai MEB. Solving Multi-Document Summarization as an Orienteering Problem. Algorithms. 2018; 11(7):96.Chicago/Turabian Style
Al-Saleh, Asma; Menai, Mohamed E.B. 2018. "Solving Multi-Document Summarization as an Orienteering Problem." Algorithms 11, no. 7: 96.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.