due to the explosive growth of the world-wide web, automatictext summarization has become an essential tool for web users. in this paperwe present a novel approach for creating text summaries. using fuzzy logicand word-net, our model extracts the most relevant sentences from an originaldocument. the approach utilizes fuzzy measures and inference on theextracted textual information from the docu...

The increasing amount of legal information available online is overwhelming for both citizens and professionals, making it difficult time-consuming to find relevant keep up with the latest developments. Automatic text summarization techniques can be highly beneficial as they save time, reduce costs, lessen cognitive load professionals. However, applying these documents poses several challenges ...

A summary is a shorter version of the original. Such a simplification highlights the major points from the much longer subject, such as a text, speech, film, or event. The purpose is to help the audience get the gist in a short period of time. Automatic summarization involves reducing a text document or a larger corpus of multiple documents into a short set of words or paragraph that conveys th...

We show some limitations of the ROUGE evaluation method for automatic summarization. We present a method for automatic summarization based on a Markov model of the source text. By a simple greedy word selection strategy, summaries with high ROUGE-scores are generated. These summaries would however not be considered good by human readers. The method can be adapted to trick different settings of ...

Automatic text summarization is a process to reduce the volume of text documents using computer programs to create a text summary with keeping the key terms of the documents. Due to cumulative growth of information and data, automatic text summarization technique needs to be applied in various domains. The approach helps in decreasing the quantity of the document without changing the context of...

Discourse markers are complex discontinuous linguistic expressions which are used to explicitly signal the discourse structure of a text. This paper describes efforts to improve an automatic tagging system which identifies and classifies discourse markers in Chinese texts by applying machine learning (ML) to the disambiguation of discourse markers, as an integral part of automatic text summariz...

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...

More and more text are available on the Internet and we need tools to tame this flow. Automatic text summarization is one solution, a text is given to the computer and it returns a non-redundant shorter text. Automatic text summarization can also be used in search engines to decrease time finding documents. To further improve search engines one can use human language technology in form of word ...

1. ABSTRACT As the amount of text available from electronic sources continues to increase, the study of automatic text summarization is more important now than it has ever been. Automatically generated summaries should be clear and concise without giving unimportant or redundant information. The process of extractive text summarization involves determining the most important sentences in a docu...

Summarization evaluation has been always a challenge to researchers in the document summarization field. Usually, human involvement is necessary to evaluate the quality of a summary. Here we present a new method for automatic evaluation of text summaries by using document graphs. Data from Document Understanding Conference 2002 (DUC-2002) has been used in the experiment. We propose measuring th...