MULTI-DOCUMENT SUMMARIZATION SYSTEM: USING FUZZY LOGIC AND GENETIC ALGORITHM

In the recent times, the requirement for generation of multi-document summary has gained a lot of attention among the researchers. Mostly, the text summarization technique uses the sentence extraction technique where the salient sentences in the multiple documents are extracted and presented as a summary. In our proposed system, we have developed a sentence extraction based automatic multi-document summarization system that employs fuzzy logic and Genetic Algorithm (GA). At first, the different features are used to identify the significance of sentences in such a way that, each sentence in the documents is specified with the feature score. The feature score is then fed to the fuzzy logic (an AI technique) in which the fuzzy inference engine decides the importance of the sentences based on the fuzzy rules. The fuzzy rules are optimized with the help of GA algorithm and the extraction of sentences can be done based on the fuzzy score of each sentences. A multi document summary is created from the extracted sentences after removing the redundant sentences. The experiments have been done using the DUC 2002 dataset and the summary is evaluated with the measures such as Precision, Recall and F-measure.