The proposed technique adopts the rough set approach of Reduct and Core calculation for a given data. Fuzzy core concept is used, when the Core is empty or whenever the Core has to be enhanced. The proposed technique is tested with DUC 2002 data Sets and has given good results.doi:10.1142/S1469026815500121R. V. V. Mu...
In this theory we cover the background theory behind a variety of methodologies for abstractive text summarization
This article proposes an extractive topic modeling-based multi-document text summarization approach for Malayalam news documents. We first cluster the contents based on latent topics identified using the latent Dirichlet allocation topic modeling technique. Then by adopting vector space model, the topic ...
The work presents a method to automatically generate a training dataset for the purpose of summarizing text documents with the help of feature extraction technique. The goal of this approach is to design a dataset which will help to perform the task of summarization very much like a human. A ...
Effective summarization of long documents is a challenging task. When addressing this challenge, Graph and Cluster-Based methods stand out as effective uns
' a novel approach to Automatic Text Summarization (ATS), capable of generating the two primary types of summaries: extractive and abstractive. We propose two distinct approaches: (1) an extractive technique (EXABSUMExtractive), which integrates statistical and semantic scoring methods to select and...
Abstractive summaries attempt to improve the coherence among sentences by eliminating redundancies and clarifying the contest of sentences. In terms of extractive summarization, sentence scoring is the technique most used for extractive text summarization. This paper describes and performs a quantitative and...
Among them, we proposed Myanmar text summarization using latent semantic analysis (LSA). Latent semantic analysis (LSA) is a technique in natural language processing,and can analyze relationships between a set of documents and the terms they contain by producing a set of concepts related to the ...
This paper focuses on extractive summarization technique. An approach for generating short and precise summary from a single document using weighted average of feature scores has been proposed. Sentences are ranked based on their scores, and top 40% sentences are selected to form the summary. ...
This method of text summarization helps to process the linguistic features of the document which is otherwise ignored in statistical summarization approaches. In this paper, we have proposed a text summarization technique by constructing lexical chains and defining a coherence metric to select the ...