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#Docear flowchart serial#
675–685 (1995)īookstein, A., Klein S.T., Raita, T.: Detecting content-bearing words by serial clustering. In: International Journal on Information Processing and Management, ACM, USA, vol. 318–327 (1994)īrandow, R., Mitze, K., Rau, L.F.: Automatic condensation of electronic publications by sentence selection. In: Proceedings of the 17th ACM-SIGIR Conference on Research and Development in Information Retrieval, New York, pp. Mittendorf, E., Schauble, P.: Document and passage retrieval based on hidden markov models. In: Proceedings of the 18th ACMSIGIR Conference on Research and Development in Information Retrieval, USA, pp.
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#Docear flowchart pdf#
Our proposed technique creates the summary by extracting sentences from the original document with the font type and pdf font or keyword extractor. Various text summarizations and text extraction techniques are being explained in this paper. It is not an easy task for human being to maintain the summary of large number of documents. Text summarization is the condensed form of any type of document whether pdf, doc, or txt files but this condensed form should preserve complete information and meaningful text with the help of single input file and multiple input file. Keyword-based summary is defined as selecting important sentences from actual text. The main focus of the paper is on the comparison between the proposed methodology keyword-based text extraction using threading and synchronization just like multiple files input as batch processing and previously used technologies for text extraction from research papers.
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