Abstract
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. Keyword-based summary is defined as selecting important sentences from actual text. 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. It is not an easy task for human being to maintain the summary of large number of documents. Various text summarizations and text extraction techniques are being explained in this paper. Our proposed technique creates the summary by extracting sentences from the original document with the font type and pdf font or keyword extractor.
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Accurate Information Extraction from Research Papers using Conditional Random Fields
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Deepak Motwani, Saxena, A.S. (2016). Multiple Document Summarization Using Text-Based Keyword Extraction. In: Pant, M., Deep, K., Bansal, J., Nagar, A., Das, K. (eds) Proceedings of Fifth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 436. Springer, Singapore. https://doi.org/10.1007/978-981-10-0448-3_15
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DOI: https://doi.org/10.1007/978-981-10-0448-3_15
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