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Pregledni rad
https://doi.org/10.32728/ric.2018.34/6

WEB BASED DOCUMENT RETRIEVAL USING ADVANCED CBRS

Shanmugasundaram Singaravelan
Anthoni Sahaya Balan
Dhanushkodi Murugan

Puni tekst: engleski, pdf (1015 KB) str. 103-116 preuzimanja: 251* citiraj
APA 6th Edition
Singaravelan, S., Balan, A.S. i Murugan, D. (2017). WEB BASED DOCUMENT RETRIEVAL USING ADVANCED CBRS. Review of Innovation and Competitiveness, 3 (4), 103-116. https://doi.org/10.32728/ric.2018.34/6
MLA 8th Edition
Singaravelan, Shanmugasundaram, et al. "WEB BASED DOCUMENT RETRIEVAL USING ADVANCED CBRS." Review of Innovation and Competitiveness, vol. 3, br. 4, 2017, str. 103-116. https://doi.org/10.32728/ric.2018.34/6. Citirano 11.08.2020.
Chicago 17th Edition
Singaravelan, Shanmugasundaram, Anthoni Sahaya Balan i Dhanushkodi Murugan. "WEB BASED DOCUMENT RETRIEVAL USING ADVANCED CBRS." Review of Innovation and Competitiveness 3, br. 4 (2017): 103-116. https://doi.org/10.32728/ric.2018.34/6
Harvard
Singaravelan, S., Balan, A.S., i Murugan, D. (2017). 'WEB BASED DOCUMENT RETRIEVAL USING ADVANCED CBRS', Review of Innovation and Competitiveness, 3(4), str. 103-116. https://doi.org/10.32728/ric.2018.34/6
Vancouver
Singaravelan S, Balan AS, Murugan D. WEB BASED DOCUMENT RETRIEVAL USING ADVANCED CBRS. Review of Innovation and Competitiveness [Internet]. 2017 [pristupljeno 11.08.2020.];3(4):103-116. https://doi.org/10.32728/ric.2018.34/6
IEEE
S. Singaravelan, A.S. Balan i D. Murugan, "WEB BASED DOCUMENT RETRIEVAL USING ADVANCED CBRS", Review of Innovation and Competitiveness, vol.3, br. 4, str. 103-116, 2017. [Online]. https://doi.org/10.32728/ric.2018.34/6

Sažetak
Multi-document summarization is an automatic procedure aimed at extraction of infor-mation from multiple texts written about the same topic. Resulting summary report al-lows individual users, such as professional information consumers, to quickly familiar-ize themselves with information contained in a large cluster of documents. This pro-posed work CBRS (Cluster Based Ranking with Significance) summarizes the multi document with semantic meaning of the terms in the documents. Such that it produces a good results while clustering and ranking with retrieving document. As a clustering result to improve or refine the sentence ranking results. The effectiveness of the pro-posed approach is demonstrated by both the cluster quality analysis and the summari-zation evaluation conducted on our simulated datasets.

Ključne riječi
Documentation Summarization; Sentence Clustering; Sentence Ranking

Hrčak ID: 191335

URI
https://hrcak.srce.hr/191335

Posjeta: 395 *