Automatic summarization is the creation of a shortened version of a text by a computer program. The product of this procedure still contains the most important points of the original text. The phenomenon of information overload has meant that access to coherent and correctlydeveloped summaries is vital. In this paper the comparison of the four systems of the automatic summarization is held and ...

Automatic text summarization has become important due to the rapid growth of information texts since it is very difficult for human beings to manually summarize large documents of texts. A full understanding of the document is essential to form an ideal summary. However, achieving full understanding is either difficult or impossible for computers. Therefore, selecting important sentences from t...

We describe the outline of Text Summarization Challenge 2 (TSC2 hereafter), a sequel text summarization evaluation conducted as one of the tasks at the NTCIR Workshop 3. First, we describe briefly the previous evaluation, Text Summarization Challenge (TSC1) as introduction to TSC2. Then we explain TSC2 including the participants, the two tasks in TSC2, data used, evaluation methods for each tas...

In this paper we present an approach to summarizing positive and negative opinions in blog threads. We first run a sentiment analysis system and consequently pass its output through a standard LSA-based text summarization system. Further on, we evaluate our approach and present the results obtained, which we believe are promising in the context of multi-document text summarization. Finally, we ...

Automatic text summarization is widely regarded as the highly difficult problem, partially because of the lack of large text summarization data set. Due to the great challenge of constructing the large scale summaries for full text, in this paper, we introduce a large corpus of Chinese short text summarization dataset constructed from the Chinese microblogging website Sina Weibo, which will be ...

Since the late 50’s and Luhn [Luh58] the information community has expressed its interest in summarizing texts. The domains of application of such methodologies are countless, ranging from news summarization [WL03, BM05, ROWBG05] to scientific article summarization [TM02] and meeting summarization [NPDP05, ELH03]. Summarization has been defined as a reductive transformation of a given set of te...