Papers by Keyword: Summarization

Abstract: With development of Internet, an increasing number of user-generated-contents provide valuable information to the public. Microblog is a new platform where peoples discuss all kinds of topics. It also provides a good opportunity for the researchers to explore the online public opinion. News collection and summarization has been attracted lots of research previously. However, manually labeling is impossible since the task is time-consuming. In this paper, we focus on news summarization with few labeled samples. A semi-supervised learning method has been proposed to tackle the problem. We employ Co-Training method to extract the news information. Posts and replies of Microblog have been identified as two independent views to train a classification model. Entity, Time, place and incident of news have been identified as well. Experimental result in different datasets shows the proposed method outperform the baseline methods.

Abstract: Video summaries provide a compact video representation preserving the essential activities of the original video, but the summaries may be confusing when mixing different activities together. Summaries Clustered methodology, showing similar activities simultaneously, enables to view much easier and more efficiently. However, it is very time consuming in generating summaries, especially in calculating motion distance and collision cost. To improve the efficiency of generating summaries, a parallel video synopsis generation algorithm is proposed based on GPGPU. The experiment result shows generation efficiency is improved greatly through GPU parallel computing. The acceleration radio can reach at 5.75 when data size is above 1600*960*30000.

Abstract: This paper proposes a special Chinese automatic summarization method based on Concept-Obtained and Improved K-means Algorithm. The idea of our approach is to obtain concepts of words based on HowNet, and use concept as feature, instead of word. We use conceptual vector space model and Improved K-means Algorithm to form a summarization. Experimental results indicate a clear superiority of the proposed method over the traditional method under the proposed evaluation scheme.

Abstract: The Digital Watermarking Technique Has Attracted Increased Interests on the past Decades. the General Framework of Robust Watermarking Is Described, and some Typical Robust Digital Image Watermarking Patents Are Surveyed in this Paper. the Main Principles and Functions of these Patents Are Reviewed and Discussed. then a Summarization about these Patents, the Challenge and Potential Research Directions in the Future Are Given Briefly.

Abstract: This paper proposes a special text summarization method based on hybrid parallel genetic algorithm. The idea of our approach is to obtain center of sentences based on k-means clustering and hybrid parallel genetic algorithm. We select those sentence according its importance and distance of center to form a summarization. Experimental results indicate a clear superiority of the proposed method over the traditional method under the proposed evaluation scheme.

Abstract: For the explosion of information in the World Wide Web, this paper proposed a new method of query-focused multi-documents summarization using genetic algorithm, search engine are used to extract relevant documents, genetic algorithm is used to extract the sentences to form a summary, and it is based on a fitness function formed by three factors: query-focused feature, importance feature, and non-redundancy feature. Experimental result shows that the proposed summarization method can improve the performance of summary, genetic algorithm is efficient.