Refine your search
Collections
Co-Authors
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Dharmadhikari, S. C.
- Context Based Topical Document Summarization
Abstract Views :194 |
PDF Views:2
Authors
Affiliations
1 Pune Institute of Computer Technology, Pune, Maharashtra, IN
1 Pune Institute of Computer Technology, Pune, Maharashtra, IN
Source
Data Mining and Knowledge Engineering, Vol 6, No 4 (2014), Pagination: 146-150Abstract
A condition of information available on the web is getting increased day by day as a result leading to information overload. To find important and useful information is becoming difficult. This growth has created a huge demand for automatic methods and tools for text summarization. In the process of text summarization, text is reduced to meaningful small size. Sentences are extracted to build summary. summary will be effective when there will be more topical terms in it. So to summarize the text or in general for proper information retrieval term weighting schemes is very important. In this paper a review of various term weighting schemes and different summarization techniques is presented. Proposed context score based text summarization model is presented.Keywords
Term Weighting, Summarization, Context Score, Information Retrieval.
- Automated Text Summarization:A Case Study for Marathi Language
Abstract Views :310 |
PDF Views:2
The Proposed framework summarizes a single document using extraction method. Before creating the summary of a text, first it is preprocessed by segmentation, tokenization, removal of stop words and stemming. In feature extraction process, the countable features like TF-ISF, sentence length, sentence positional value, SOV verification are used to make the summary more relevant and precise. For stemming purpose we develop a rule based as well as directory based Marathi Stemmer.
Authors
Affiliations
1 Department of Information Technology, Pune Institute of Computer Technology, Pune, IN
1 Department of Information Technology, Pune Institute of Computer Technology, Pune, IN
Source
Data Mining and Knowledge Engineering, Vol 6, No 3 (2014), Pagination: 99-105Abstract
The amount of information on the Internet/Web is growing day by day, which has caused information overload. To find relevant useful information is becoming crucial task. This growth has created a huge demand for automatic methods and tools for text summarization. In Natural Language Processing, Text summarization is an area getting attention of lots of researcher. In this paper, we present a survey on text summarization techniques, also discuss the key morphology of Marathi Languages and proposed framework of Text Summarization. Last decade, lots of work done on English language text summarization but a few notable works have been done for Marathi Language.The Proposed framework summarizes a single document using extraction method. Before creating the summary of a text, first it is preprocessed by segmentation, tokenization, removal of stop words and stemming. In feature extraction process, the countable features like TF-ISF, sentence length, sentence positional value, SOV verification are used to make the summary more relevant and precise. For stemming purpose we develop a rule based as well as directory based Marathi Stemmer.