- author = "Arman Kiani-B and M. R. Akbarzadeh-T",
- title = "Automatic Text Summarization Using: Hybrid Fuzzy GA-GP",
- booktitle = "Proceedings of the 2006 IEEE Congress on Evolutionary Computation",
- year = "2006",
- editor = "Gary G. Yen and Lipo Wang and Piero Bonissone and Simon M. Lucas",
- pages = "5465--5471",
- address = "Vancouver",
- month = "16-21 " # jul,
- publisher = "IEEE Press",
- keywords = "genetic algorithms, genetic programming",
- ISBN = "0-7803-9487-9",
-
DOI = "
doi:10.1109/FUZZY.2006.1681829",
- size = "7 pages",
- abstract = "A novel technique is proposed for summarising text using a combination of Genetic Algorithms (GA) and Genetic Programming (GP) to optimise rule sets and membership functions of fuzzy systems. The novelty of the proposed algorithm is that fuzzy system is optimized for extractive based text summarizing. In this method GP is used for structural part and GA for the string part (Membership functions). The goal is to develop an optimal intelligent system to extract important sentences in the texts by reducing the redundancy of data. The method is applied in 3 test documents and compared with the standard fuzzy systems as well as two other commercial summarisers: Microsoft word and Copernic Summarizer. Simulations demonstrate several significant improvements with the proposed approach.",
-
notes = "WCCI 2006 - A joint meeting of the IEEE, the EPS, and
the IEE.
IEEE Catalog Number: 06TH8846D",
