Abstract
Nowadays, with increasing volume of electronic text information, the need for production of summary systems becomes essential. Summary systems capture and summarize the most important concepts of the documents and help the user to go through the main points of the text faster and make the processing of information much easier. An important class of such systems is the ones that produce extractive summaries. This summary is produced by selecting most important parts of the document without doing any modification on the main text. One approach for producing this kind of summary is using the graph theory. In this paper a new algorithm based on the graph theory is introduced to select the most important sentences of the document. In this algorithm the nodes and edges will be assigned with different weights and then the final weight of each one will be defined by combining these values. This final weight indicates the importance of the sentence and the probability of appearing this sentence in the final summary. The results show that considering simultaneous different criteria generate a summary which is more similar to human one.
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Shakeri, H., Gholamrezazadeh, S., Salehi, M.A., Ghadamyari, F. (2012). A New Graph-Based Algorithm for Persian Text Summarization. In: J. (Jong Hyuk) Park, J., Chao, HC., S. Obaidat, M., Kim, J. (eds) Computer Science and Convergence. Lecture Notes in Electrical Engineering, vol 114. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2792-2_3
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DOI: https://doi.org/10.1007/978-94-007-2792-2_3
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