A sentence selection model and HLO algorithm for extractive text summarization
作者： Rasim Alguliyev , Ramiz Aliguliyev , Nijat Isazade
DOI: 10.1109/ICAICT.2016.7991686
关键词: Automatic summarization 、 Natural language processing 、 Computer science 、 Machine learning 、 Semantics (computer science) 、 Process (engineering) 、 Linear programming 、 Optimization problem 、 Artificial intelligence 、 Redundancy (engineering) 、 Sentence 、 Selection (genetic algorithm)
摘要: In paper text summarization represented as a sentence scoring and selection process. The process is modeled multi-objective optimization problem. proposed model attempts to find balance between coverage redundancy in summary. For solving the problem human learning algorithm utilized.
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