Computational models for text summarization

نویسندگان

  • Leonid Keselman
  • Ludwig Schubert
چکیده

Abstractive text summarization is a blossoming area of natural language processing research in which short textual summaries are generated from longer input documents. Existing state-of-the-art methods take long time to train, and are limited to functioning on relatively short input sequences. We evaluate neural network architectures with simplified encoder stages, which naturally support arbitrarily long input sequences in a computationally efficient manner.ive text summarization is a blossoming area of natural language processing research in which short textual summaries are generated from longer input documents. Existing state-of-the-art methods take long time to train, and are limited to functioning on relatively short input sequences. We evaluate neural network architectures with simplified encoder stages, which naturally support arbitrarily long input sequences in a computationally efficient manner.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A survey on Automatic Text Summarization

Text summarization endeavors to produce a summary version of a text, while maintaining the original ideas. The textual content on the web, in particular, is growing at an exponential rate. The ability to decipher through such massive amount of data, in order to extract the useful information, is a major undertaking and requires an automatic mechanism to aid with the extant repository of informa...

متن کامل

EXTRACTION-BASED TEXT SUMMARIZATION USING FUZZY ANALYSIS

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...

متن کامل

Systematic literature review of fuzzy logic based text summarization

Information Overloadrq  is not a new term but with the massive development in technology which enables anytime, anywhere, easy and unlimited access; participation & publishing of information has consequently escalated its impact. Assisting userslq    informational searches with reduced reading surfing time by extracting and evaluating accurate, authentic & relevant information are the primary c...

متن کامل

Text Summarization Using Cuckoo Search Optimization Algorithm

Today, with rapid growth of the World Wide Web and creation of Internet sites and online text resources, text summarization issue is highly attended by various researchers. Extractive-based text summarization is an important summarization method which is included of selecting the top representative sentences from the input document. When, we are facing into large data volume documents, the extr...

متن کامل

Biogeography-Based Optimization Algorithm for Automatic Extractive Text Summarization

    Given the increasing number of documents, sites, online sources, and the users’ desire to quickly access information, automatic textual summarization has caught the attention of many researchers in this field. Researchers have presented different methods for text summarization as well as a useful summary of those texts including relevant document sentences. This study select...

متن کامل

Experiences with and Reflections on Text Summarization Tools

Text summarization is a process of distilling the most important content from text documents. While human beings have proven to be extremely capable summarizers, computer based automatic abstracting and summarizing has proven to be extremely challenging tasks. In this paper we report our experience with applying extractive summarization techniques to process news articles, economic reports and ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017