Text Summarization is condensing the source text into shorter form and retaining its information content and overall meaning. Punjabi text Summarization system is text extraction based summarization system which is used to summarize the Punjabi text by retaining relevant sentences based on statistical and linguistic features of text. Punjabi text summarization system is available online at webs...

This paper describes the followed methodology to automatically generate titles for a corpus of questions that belong to sociological opinion polls. Titles for questions have a twofold function: (1) they are the input of user searches and (2) they inform about the whole contents of the question and possible answer options. Thus, generation of titles can be considered as a case of automatic summa...

In this new era, where tremendous information is available on the internet. It is most important to provide the improved mechanism to extract the information quickly and accurately. This leads to the difficulty for human beings to manually extract the summary of large documents of text. There is plenty of text material available on web. The difficulty is in looking for the exact document from t...

In this paper we investigate how participant involvement and turn-taking features relate to extractive summarization of meeting dialogues. In particular, we examine whether automatically derived measures of group level involvement, like participation equality and turn-taking freedom, can help detect where summarization relevant meeting segments will be. Results show that classification using tu...

Lexical Cohesion is a commonly studied linguistic feature as it is easily identified from the surface of a text. However, the purposes for studying lexical cohesion are varied, and each purpose requires different methods. This study analyzes two short movie review texts for four different research purposes using lexical cohesion: text evaluation, text segmentation, text summarization, and text ...

In recent years, there has been a explosion in the amount of text data from a variety of sources. This volume of text is an invaluable source of information and knowledgewhich needs to be effectively summarized to be useful. In this review, the main approaches to automatic text summarization are described. We review the different processes for summarization and describe the effectiveness and sh...

In this paper, we put forward UIDS, a new high-performing extensible framework for extractive MultiLingual Document Summarization. Our approach looks on a document in a multilingual corpus as an item sequence set, in which each sentence is an item sequence and each item is the minimal semantic unit. Then we formalize the extractive summary as summary diversity sampling problem that considers to...

This paper presents a knowledge-poor method for the solution of anaphoric and deictic expressions in Dutch texts. The method is developed for use in a text summarization system. Anaphora resolution plays an important role in the analysis of the original text as well as in the generation of the text summary.

In this paper, we introduce a large-scale test collection for multiple document summarization, the Text Summarization Challenge 3 (TSC3) corpus. We detail the corpus construction and evaluation measures. The significant feature of the corpus is that it annotates not only the important sentences in a document set, but also those among them that have the same content. Moreover, we define new eval...

Lot of work has already been done for automatic text summarization. In this paper we have given a novel statistical approach to summarize the given Odia text. In our approach extraction of relevant sentences is done which can give the actual concept of the input document in a concise form. We rank each sentence in the document by assigning a weight value to each word of the sentence. The senten...