Multi-document summarization

About: Multi-document summarization is a research topic. Over the lifetime, 2270 publications have been published within this topic receiving 71850 citations.

Investigations on Event-Based Summarization

Abstract: We investigate independent and relevant event-based extractive mutli-document summarization approaches. In this paper, events are defined as event terms and associated event elements. With independent approach, we identify important contents by frequency of events. With relevant approach, we identify important contents by PageRank algorithm on the event map constructed from documents. Experimental results are encouraging.

WordNet-based Summarization to Enhance Learning Interaction Tutoring

Abstract: The process of summarizing information is becoming increasingly important in the light of recent advances in resource creation/distribution technology and the resulting infux of large amounts of information in everyday life. These advances are also challenging educational institutions to adopt the opportunities of distributed knowledge sharing and communication. The paper describes a summarization system to support tutors in managing student communication and interaction within a learning framework. Results show the adequacy of the system in identifying a good content summarization and then in improving the effciency and effectiveness of the context in which summarization can be integrated.

Indexing of Arabic documents automatically based on lexical analysis

Abstract: The continuous information explosion through the Internet and all information sources makes it necessary to perform all information processing activities automatically in quick and reliable manners. In this paper, we proposed and implemented a method to automatically create and Index for books written in Arabic language. The process depends largely on text summarization and

Video Summarization: Survey on Event Detection and Summarization in Soccer Videos

Abstract: In today's world, the rapid development of digital video and editing technology has led to fast growing of video data, creating the need for effective and advanced techniques for analysis and video retrieval, as multimedia repositories have made browsing, delivery of contents (video) and video retrieval very slow. Hence, video summarization proposes various ways for faster browsing among a large amount of data and also for content indexing. Many people spend their free time to watch or play different sports like soccer, cricket, etc. but it is not possible to watch each and every game due to the longer timing of the game. In such cases, the users may just want to view the summary of the video that is just an abstract of the original video, instead of watching the whole video that provides more information about the occurrence of various incidents in the video. It is preferable to watch just highlights of the game or just review/trailer of a movie. Apparently, summarizing a video is an important process. In this paper, video summarization approaches are discussed, that can generate static or dynamic summaries. We present different techniques for each mode in literature. We have discussed some features used for generating video summaries. As soccer is the world’s most famous game played and watched, it is taken as a case study. Research done in this domain is discussed. We conclude that there is a broad perspective for further research in this field.

AHP Techniques for Persian Text Summarization

Abstract: In recent years, there has been an increasing amount of information on the web. Some of essential resources to shorten text documents use summarization technologies. In this paper, we present an AHP technique for Persian Text Summarization. This proposed model uses analytical hierarchy as a base factor for an evaluation algorithm and improves the summarization quality of Persian language text. The weighting and combination methods are two main contributions of the proposed text evaluation algorithm.