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Automatic Key Term Extraction from Research Article using Hybrid Approach
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 166 - Number 6 |
| Year of Publication: 2017 |
| Authors: Selvani Deepthi Kavila, B. Rajesh, N. Vyshnavi, K. Moni Sushma Deep |
10.5120/ijca2017914039
|
Selvani Deepthi Kavila, B. Rajesh, N. Vyshnavi, K. Moni Sushma Deep . Automatic Key Term Extraction from Research Article using Hybrid Approach. International Journal of Computer Applications. 166, 6 ( May 2017), 17-21. DOI=10.5120/ijca2017914039
Abstract
Key terms are subset of terms or phrases from an article that can describe the meaning of the article. In our information era, key information terms are very useful for information retrieval, article retrieval, article clustering, summarization, text mining, and text clustering and so on. These are the set of terms from an article that can describe the meaning of the article. The main aim of this paper is to help the users to quickly extract the key information automatically using hybrid systems from an article which convey the complete meaning of the text and then extracts the algorithm name present in the research paper. The focus of Hybrid system is to automatically extract the key information from various articles. Vital terms from articles are extracted by using Linguistics approaches and Statistical approaches. These terms are then passed to a rule-based extractor for further refinement where a statistical analysis is made on this set of terms according to different range of classes. Finally, this set is passed to the Multi-layered Feed Forward Artificial Neural Networks where the key information terms are extracted by using back propagation. Based on the performance evaluation, it has been observed that the acquired results are efficient when compared to manual judgement.
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