Automatic Text Summarization Using Hybrid Fuzzy GA-GP

Kiani-B, Arman; Akbarzadeh-T, Mohammad-R.

doi:10.1109/fuzzy.2006.1681829

Cited by 38 publications

(14 citation statements)

References 14 publications

(22 reference statements)

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“…TotalSimsemantic(S1,S2)=a*Simsemantic(S1,S2)+(1-a) SimWordOrder (S1,S2) (7) In [18] and [19] it is proven that the combination of parameters is greater than the syntax parameter, and thus is the best evaluation of sentence similarity. The parameter a in our experiments takes 0.8 in the above equation.…”

Section: Combination Of Parametersmentioning

confidence: 99%

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Automatic text summarization using fuzzy inference

Jafari

Wang

Qin

et al. 2016

2016 22nd International Conference on Automation and Computing (ICAC)

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Abstract-Due to the high volume of information and electronic documents on the Web, it is almost impossible for a human to study, research and analyze this volume of text. Summarizing the main idea and the major concept of the context enables the humans to read the summary of a large volume of text quickly and decide whether to further dig into details. Most of the existing summarization approaches have applied probability and statistics based techniques. But these approaches cannot achieve high accuracy. We observe that attention to the concept and the meaning of the context could greatly improve summarization accuracy, and due to the uncertainty that exists in the summarization methods, we simulate human like methods by integrating fuzzy logic with traditional statistical approaches in this study. The results of this study indicate that our approach can deal with uncertainty and achieve better results when compared with existing methods.

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Section: Combination Of Parametersmentioning

confidence: 99%

“…In [6], [7], methods for text-based summarization by using the fuzzy logic and fuzzy inference system are presented. Genetic Algorithm and Genetic Programming are also used to optimize the rule sets and membership functions of the fuzzy system.…”

Section: Related Workmentioning

confidence: 99%

Automatic text summarization using fuzzy inference

Jafari

Wang

Qin

et al. 2016

2016 22nd International Conference on Automation and Computing (ICAC)

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“…In their research they discussed about the techniques to achieve readable and coherent summaries. Arman Kiani et al [5] proposed Text summarization using Hybrid Fuzzy systems which is based on summarizing a text on the fusion of Genetic System. Saeedeh Gholamrezazadeh et al [6] presented different types of summarization methods and a common summarized system was implemented.…”

Section: A Back Ground Work Related To Document Summarizationmentioning

confidence: 99%

Extractive Text Summarization Using Modified Weighing and Sentence Symmetric Feature Methods

Kavila¹,

Radhika²

2015

IJMECS

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Abstract-TextSummarization is a process that converts the original text into summarized form without changing the meaning of its contents. It finds its usefulness in many areas when the time to go through a large content is limited. This paper presents a comparative evaluation of statistical methods in extractive text summarization. Top score method is taken to be the bench mark for evaluation. Modified weighing method and modified sentence symmetric feature method are implemented with additional characteristic features to achieve a better performance than the benchmark method. Thematic weight and emphasize weights are added to conventional weighing method and the process of weight updation in sentence symmetric method is also modified in this paper. After evaluating these three methods using the standard measures, modified weighing method is identified as the best method with 80% efficiency.

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“…Applying the fuzzy logic for text summarization still needs more investigation; a few studies were done in this direction, here we present some works which used fuzzy IF-THEN rules for scoring the sentences, Kiani-B and Akbarzadeh-T [15] presented text summarization system in which the features are used as input for the fuzzy system, based on the fuzzy rules each sentence receives score in the range between zero and one, the fuzzy rules were optimized using hybrid GA and GP. Kyoomarsi et al [16] proposed fuzzy logic based text summarization, following Kiani-B and Akbarzadeh-T's way [15] , the difference between these two studies is in the later, the fuzzy rules were not optimized.…”

Section: Introductionmentioning

confidence: 99%

“…Kyoomarsi et al [16] proposed fuzzy logic based text summarization, following Kiani-B and Akbarzadeh-T's way [15] , the difference between these two studies is in the later, the fuzzy rules were not optimized.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Swarm Based Text Summarization

Binwahlan¹,

Salim²,

Suanmali³

2009

J. of Computer Science

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Problem statement:The aim of automatic text summarization systems is to select the most relevant information from an abundance of text sources. A daily rapid growth of data on the internet makes the achieve events of such aim a big challenge. Approach: In this study, we incorporated fuzzy logic with swarm intelligence; so that risks, uncertainty, ambiguity and imprecise values of choosing the features weights (scores) could be flexibly tolerated. The weights obtained from the swarm experiment were used to adjust the text features scores and then the features scores were used as inputs for the fuzzy inference system to produce the final sentence score. The sentences were ranked in descending order based on their scores and then the top n sentences were selected as final summary. Results:The experiments showed that the incorporation of fuzzy logic with swarm intelligence could play an important role in the selection process of the most important sentences to be included in the final summary. Also the results showed that the proposed method got a good performance outperforming the swarm model and the benchmark methods. Conclusion: Incorporating more than one technique for dealing with the sentence scoring proved to be an effective mechanism. The PSO was employed for producing the text features weights. The purpose of this process was to emphasize on dealing with the text features fairly based on their importance and to differentiate between more and less important features. The fuzzy inference system was employed to determine the final sentence score, on which the decision was made to include the sentence in the summary or not.

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Automatic Text Summarization Using Hybrid Fuzzy GA-GP

Cited by 38 publications

References 14 publications

Automatic text summarization using fuzzy inference

Automatic text summarization using fuzzy inference

Extractive Text Summarization Using Modified Weighing and Sentence Symmetric Feature Methods

Fuzzy Swarm Based Text Summarization

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