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The efficiency and scalability of the proposed scheme is analyzed and compared with standard algorithms such as SOM, DASOM and Linear Regression analysis. The system is trained and tested on DBLP database, University of Trier, Germany. The superiority of hybrid DASOM algorithm over the well-known algorithms in handling high dimensional large-scale data to detect emergent trends from the corpus is established in this article.<\/p>","DOI":"10.4018\/ijiit.2019070104","type":"journal-article","created":{"date-parts":[[2019,5,28]],"date-time":"2019-05-28T21:10:32Z","timestamp":1559077832000},"page":"64-78","source":"Crossref","is-referenced-by-count":2,"title":["Text Clustering Using PSO Based Dynamic Adaptive SOM for Detecting Emergent Trends"],"prefix":"10.4018","volume":"15","author":[{"family":"Chandrakala D","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Kumaraguru College of Technology, Coimbatore, India"}]},{"family":"Sumathi S","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronics Engineering, PSG College of Technology, Coimbatore, India"}]},{"family":"Saran Kumar A","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, India"}]},{"family":"Sathish J","sequence":"additional","affiliation":[{"name":"Senior Software Engineer, Capgemini, India"}]}],"member":"2432","reference":[{"key":"IJIIT.2019070104-0","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-04125-9_28"},{"key":"IJIIT.2019070104-1","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2004.4"},{"key":"IJIIT.2019070104-2","doi-asserted-by":"crossref","unstructured":"Adeva, J. 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