We are working on a selective approach for document summarization. It is based on the topics(concepts or phrases) and at the sentence level. I am wondering if anyone is familiar with any available other approaches or techniques for summarization.
Dear Mostafa,
Some other possible approaches of summarization can be by using:
(1) Natural language processing
See for example:
Haque, M. M., Pervin, S., & Begum, Z. (2013). Literature review of automatic multiple documents text summarization. International Journal of Innovation and Applied Studies, Innovative Space of Scientific Research Journals, 3, 121-129.
Jagadeesh, J., & Varma, V. (2005). Single Document Summarization Using Natural Language Processing. In IICAI (pp. 741-748).
Prabhala, B. (2014). Scalable Multi-Document Summarization Using Natural Language Processing (Doctoral dissertation, Rochester Institute of Technology).
(2) Keyword Extraction
See for example:
Matsuo, Y., & Ishizuka, M. (2004). Keyword extraction from a single document using word co-occurrence statistical information. International Journal on Artificial Intelligence Tools, 13(01), 157-169.
Ma, L., He, T., Li, F., Gui, Z., & Chen, J. (2008, December). Query-focused multi-document summarization using keyword extraction. In Computer Science and Software Engineering, 2008 International Conference on (Vol. 1, pp. 20-23). IEEE.
(3) Diagram summarization
See for example:
Futrelle, R. P. (1999). Summarization of diagrams in documents. Advances in Automated Text Summarization, 403-421.
Best regards,
Yaakov
- Badges
- Science topic
- Similar topics
- Biological Science
- Physiology
- Physiological Processes
- Stress