Usually, presence of the same information in multiple documents is the main problem faced in effective information access. Instead of this redundant information thus accessed or retrieved, users are interested in retrieving information that addresses one or other several aspects. In such situation, text summarization proves to be very useful. Not only in Information retrieval, but it is an extr...

Due to the rapid development of internet technology, social media and popular research article databases have generated many open text information. This large amount textual information leads 'Big Data'. Textual can be recorded repeatedly about an event or topic on different websites. Text summarization (TS) is emerging field that helps produce summary from a single multiple documents. The redu...

University of Ljubljana Faculty of Computer and Information Science Ercan Canhasi Graph-based models for multi-document summarization is thesis is about automatic document summarization, with experimental results on general, query, update and comparative multi-document summarization (MDS). We describe prior work and our own improvements on some important aspects of a summarization system, incl...

As the amount of information on the Web grows, the ability to retrieve relevant information quickly and easily is necessary. The combination of ample news sources on the Web, little time to browse news, and smaller mobile devices motivates the development of automatic highlight extraction from single news articles. Our system, NetSum, is the first system to produce highlights of an article and ...

Summarization systems and Question Answering systems can be treated to have complementary functionality to each other. For instance, a question answering system could have a summarization module, that can summarize the fragments of answers found by the question answering system. On the other hand a summarization system can be given a question as input, to generate a question focused summary as ...

In this paper, we introduce and compare between two novel approaches, supervised and unsupervised, for identifying the keywords to be used in extractive summarization of text documents. Both our approaches are based on the graph-based syntactic representation of text and web documents, which enhances the traditional vector-space model by taking into account some structural document features. In...

Title of dissertation: Text Summarization Evaluation: Correlating Human Performance on an Extrinsic Task with Automatic Intrinsic Metrics Stacy F. Hobson Doctor of Philosophy, 2007 Dissertation directed by: Professor Bonnie J. Dorr Department of Computer Science Text summarization evaluation is the process of assessing the quality of an individual summary produced by human or automatic methods....