Text Summarization within the Latent Semantic Analysis Framework: Comparative Study
نویسندگان
چکیده
منابع مشابه
Comparative summarization via Latent Semantic Analysis
The primary focus of this paper is multi-document comparative summarization. At first, the concept of comparative summarization is defined, and then the existing approaches are described. Finally, a new method using LSA (Latent Semantic Analysis) for comparative summarization is proposed. Key-Words: Comparative summarization, contrastive summarization, summarization via LSA
متن کاملUsing Latent Semantic Analysis in Text Summarization and Summary Evaluation
This paper deals with using latent semantic analysis in text summarization. We describe a generic text summarization method which uses the latent semantic analysis technique to identify semantically important sentences. This method has been further improved. Then we propose two new evaluation methods based on LSA, which measure content similarity between an original document and its summary. In...
متن کاملText summarization using a trainable summarizer and latent semantic analysis
This paper proposes two approaches to address text summarization: modified corpus-based approach (MCBA) and LSA-based T.R.M. approach (LSA+T.R.M.). The first is a trainable summarizer, which takes into account several features, including position, positive keyword, negative keyword, centrality, and the resemblance to the title, to generate summaries. Two new ideas are exploited: (1) sentence po...
متن کاملText Summarization of Turkish Texts using Latent Semantic Analysis
Text summarization solves the problem of extracting important information from huge amount of text data. There are various methods in the literature that aim to find out well-formed summaries. One of the most commonly used methods is the Latent Semantic Analysis (LSA). In this paper, different LSA based summarization algorithms are explained and two new LSA based summarization algorithms are pr...
متن کاملUsing Latent Semantic Analysis for Extractive Summarization
In this paper, we use simple techniques derived from on Latent Semantic Analysis (LSA) to provide a simple and robust way of generating extractive summaries for TAC 2008 Update Summarization task.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2013
ISSN: 0975-8887
DOI: 10.5120/14060-2366