AMDS: Sentence Extraction Based Proficient Framework for Multi-Document Summarization
- DOI
- 10.2991/icaise.2013.20How to use a DOI?
- Keywords
- Sentence extraction, Multi-document summarization, Sentence ingenious ranking, Similarity measure.
- Abstract
Rapid improvement of electronic documents in World Wide Web has made overload to the users in accessing the information. Therefore, abstracting the primary content from numerous documents related to same topic is highly essential. Summarization of multiple documents helps in valuable decision-making in less time. This paper proposed a framework named Adept Multi-Document Summarization (AMDS) for efficient summarization of document, which achieves the aforementioned requirement. Here, the documents are preprocessed initially to remove the information that is less important. Summary of each preprocessed document is obtained through the sentence extraction process. Single document summarization is carried out based on graph model. A ranking method named Ingenious Ranking (IR) is proposed to rank and order the extracted single document summaries. It ranks the sentences in the generated summaries of each document and incorporates the individual summaries to generate a concise summary. Empirical results presented in this paper demonstrate the efficiency of the proposed AMDS framework.
- Copyright
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - C. Balasubramanian AU - K.G. Srinivasagan AU - S. Geetha PY - 2013/08 DA - 2013/08 TI - AMDS: Sentence Extraction Based Proficient Framework for Multi-Document Summarization BT - Proceedings of the 2013 The International Conference on Artificial Intelligence and Software Engineering (ICAISE 2013) PB - Atlantis Press SP - 87 EP - 94 SN - 1951-6851 UR - https://doi.org/10.2991/icaise.2013.20 DO - 10.2991/icaise.2013.20 ID - Balasubramanian2013/08 ER -