[PDF] Top 20 An Evolutionary Algorithm for Automatic Summarization

... multi-document summarization. The second is dedicated to update summarization: the goal is to summarize information in the update set, as- suming that the user has already read the infor- mation in the ... See full document

... While the second step is straight forward, the first step needs more attention. Finding all frequent item sets in a database is difficult since it involves searching all possible item sets (item combinations). The set of ... See full document

... The problem of building an automatic fitness function is obvious. How can we with computer code reflect things as sensibility, intensity, musicality, tension, expectation, climax, relaxation etc., i.e. concepts ... See full document

... of automatic topic detection in text ...clustering algorithm to group the semantically-related ...An automatic text summarization system using a topic strength method was used to compare the ... See full document

... an automatic text summarization system by combining both a statistical approach and a neural ...genetic algorithm (GA) and mathematical regression (MR) in order to obtain a suitable combination of ... See full document

... One of the most well-known extractive ap- proaches is maximal marginal relevance (MMR), which scores each textual unit and extracts the unit that has the highest score in terms of the MMR cri- teria (Goldstein et al., ... See full document

... [7] Yi Guo and George Stylios, An Intelligent Algorithm For Automatic Document Summarization [8] Monika Arora, Uma Kanjilal, Dinesh Varshney, “Efficient and Intelligent Information Retri[r] ... See full document

... based algorithm for unsupervised summarization, which was successfully used in the past for the summarization of short ...centrality algorithm is then applied on the graph ... See full document

... of automatic text summarization within the Natural Language Processing (NLP) ...an algorithm that can recognize the action word by abstraction and summarize the input document by extraction and ... See full document

... an automatic summarization system of news text with the use of LSA as a way to identify the important topics in the documents without using lexical resources like ...ranking algorithm is then applied ... See full document

... Text summarization is one of the applications of information retrieval, which is the method of condensing the input text into a shorter version, preserving its information content and overall ...specific ... See full document

... text summarization algorithm is proposed by Amulfo et al [12], which use n-grams and maximal frequent word sequences as features in a vector space ...ranking algorithm is proposed by Amini et al [13] ... See full document

... an algorithm. The algorithm takes two input parameters: the input text document and number of frequent ...This algorithm is applied here for single document, it can be applied for multi ...text ... See full document

... As shown in the table, the average silhouette score is derived from the calculation based on the similarity definition obtained by the ontology- based vector space model. We achieved a high sil- houette score of 0.9878, ... See full document

... Test summarization is a process of extracting large and useful information from original documents and represent it in the summary/ abstract ...text summarization. Automatic text summarization ... See full document

... Abstract— Automatic text summarization system generates summaries or abstract of large ...for summarization of text in various ...based algorithm is sufficient for agglutinative language like ... See full document

... So by reviewing the work done in [2, 5, 7, 8-10, 11], we conclude that all the recent well-known methods are pretty good efficient for cut detection but in other side their response towards gradual transition is not that ... See full document

... proposed automatic text summarization studies built based on optimization techniques is included in the concept of the ...DE algorithm and test its performance in non-numerical datasets (text ... See full document

... timelime summarization is firstly proposed by Allan et ...the evolutionary character- istics of ...ranking algorithm used in traditional multi-document summarization (MDS) to timeline ... See full document

... All summarization methods have parameters that influence the quality of the ...genetic algorithm (GA) can be efficient for this kind of ...optimize summarization methods ... See full document