Multi-document extractive text summarization based on firefly algorithm
| Autor: | Manoj Kumar, Minakshi Tomer |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
Fitness function
General Computer Science Relation (database) Computer science Particle swarm optimization 020206 networking & telecommunications Cohesion (computer science) 02 engineering and technology computer.software_genre Swarm intelligence Automatic summarization Genetic algorithm ComputingMethodologies_DOCUMENTANDTEXTPROCESSING 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Firefly algorithm Data mining computer |
| Zdroj: | Journal of King Saud University - Computer and Information Sciences. 34:6057-6065 |
| ISSN: | 1319-1578 |
| DOI: | 10.1016/j.jksuci.2021.04.004 |
| Popis: | Extracting relevant information from a large amount of data is a challenging task. Automatic text summarization is a potential solution for obtaining this information. In this paper, a nature inspired swarm intelligence-based algorithm viz. firefly algorithm for multi-document text summarization is proposed. A new fitness function consisting of three features viz. topic relation factor, cohesion factor and readability factor is utilized. The experiments are performed on datasets from Document Understanding Conference i.e. DUC-2002, DUC-2003 and DUC-2004. The performance of the algorithm has been evaluated using ROUGE score. The performance of the proposed algorithm is compared with some other nature inspired ones such as particle swarm optimization (PSO) and genetic algorithm (GA). The performance of the proposed algorithm outperforms the other adopted ones. |
| Databáze: | OpenAIRE |
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