کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6899127 | 1446467 | 2017 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Bio-inspired approaches for extractive document summarization: AÂ comparative study
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موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی (عمومی)
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
With the exponential growth of information in World Wide Web, extracting relevant information from huge amount of data has become a critical task. Text summarization has been appeared as one of the solution to such problem. As the main objective is to retrieve a condensed document that pertain the original information, so it can be considered as an optimization problem. In this paper, a comparative analysis of few meta-heuristic approaches such as Cuckoo Search (CS), Cat Swarm Optimization (CSO), Particle Swarm Optimization (PSO), Harmony Search (HS), and Differential Evolution (DE) algorithm is presented for single document summarization problem. The performance of all these algorithms are compared in terms of different evaluation metrics such as F score, true positive rate and positive predicate value to validate summary relevancy and non-redundancy over traditional and standard Document Understanding Conference (DUC) datasets.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Karbala International Journal of Modern Science - Volume 3, Issue 3, July 2017, Pages 119-130
Journal: Karbala International Journal of Modern Science - Volume 3, Issue 3, July 2017, Pages 119-130
نویسندگان
Rasmita Rautray, Rakesh Chandra Balabantaray,