Abstractive summarization is the popular research topic nowadays. Due to the difference in language property, Chinese summarization also gains lots of attention. Most of studies use character-based representation instead of word-based to keep out the error introduced by word segmentation and OOV problem. However, we believe that word-based representation can capture the semantics of the article...

Automatic summarization [5] can be defined as the procedure to create a short version of a text by a computer program. Its product still contains the most important points of the existing text. Multi-document summarization [6] can be defined as an automatic procedure which extracts information from multiple texts that is written about the same topic. Resulting summary report allows individual u...

Text summarization is the process of extracting salient information from the source text and to present that information to the user in the form of summary. It is very difficult for human beings to manually summarize large documents of text. Automatic abstractive summarization provides the required solution but it is a challenging task because it requires deeper analysis of text. In this paper,...

Automatic text summarization is a technique concerning the creation of a compressed form for single document or multidocuments. The summary creation under the condition of the redundancy and the summary length limitation is a challenge problem. The automatic text summarization system which is built based on exploiting of the advantages of different resources in form of an integration model coul...

The goal of automatic text summarization is to reduce the size of a document while preserving its content. We investigate a summarization method which uses not only statistical features but also the contextual meaning of documents by using lexical clustering. We present a new method to compute lexical cluster in a text without high cost knowledge resources; the WordNet thesaurus. Summarization ...

The biomedical community makes extensive use of text mining technology. In the past several years, enormous progress has been made in developing tools and methods, and the community has been witness to some exciting developments. Although the state of the community is regularly reviewed, the sheer volume of work related to biomedical text mining and the rapid pace in which progress continues to...

The task of automatic text summarization consists of generating a summary of the original text that allows the user to obtain the main pieces of information available in that text, but with a much shorter reading time. This is an increasingly important task in the current era of information overload, given the huge amount of text available in documents. In this paper the automatic text summariz...

We have explored the usefulness of incorporating speech and discourse features in an automatic speech summarization system applied to meeting recordings from the ICSI Meetings corpus. By analyzing speaker activity, turn-taking and discourse cues, we hypothesize that such a system can outperform solely text-based methods inherited from the field of text summarization. The summarization methods a...

Proper evaluation is crucial for developing high-quality computerized text summarization systems. In the clinical domain, the specialized information needs of the clinicians complicates the task of evaluating automatically produced clinical text summaries. In this paper we present and compare the results from both manual and automatic evaluation of computer-generated summaries. These are compos...

Automatic video summarization has become an active research topic in content-based video processing. However, not much emphasis has been placed on developing rigorous summary evaluation methods and developing summarization systems based on a clear understanding of user needs, obtained through user centered design. In this paper we address these two topics and propose an automatic video summary ...