ExB Text Summarizer

نویسندگان

  • Stefan Thomas
  • Christian Beutenmüller
  • Xose de la Puente
  • Robert Remus
  • Stefan Bordag
چکیده

We present our state of the art multilingual text summarizer capable of single as well as multi-document text summarization. The algorithm is based on repeated application of TextRank on a sentence similarity graph, a bag of words model for sentence similarity and a number of linguistic preand post-processing steps using standard NLP tools. We submitted this algorithm for two different tasks of the MultiLing 2015 summarization challenge: Multilingual Singledocument Summarization and Multilingual Multi-document Summarization.

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

ExB Medical Text Miner

We present ExB Medical Text Miner – a text mining pipeline for processing biomedical documents. This application employs stateof-the-art Named Entity Recognition, using linguistic features and word embeddings in a fully-connected second-order Conditional Random Field model, as well as a novel two-stage Relation Extraction module that first detects entity-level relations using a Support Vector C...

متن کامل

Development of a Swedish Corpus for Evaluating Summarizers and other IR-tools

We are presenting the construction of a Swedish corpus aimed at research on Information Retrieval, Information Extraction, Named Entity Recognition and Multi Text Summarization, we will also present the results on evaluating our Swedish text summarizer SweSum with this corpus. The corpus has been constructed by using Internet agents downloading Swedish newspaper text from various sources. A sma...

متن کامل

Query-Based Summarizer Based on Similarity of Sentences and Word Frequency

Text summarization is the most challenging task in information retrieval tasks. It is an outcome of electronic document explosion and can be seen as the condensation of the document collection. The use of text summarization allows a user to get a sense of the content of full-text, or to know its information content without reading all sentences within the full-text. Data reduction helps user to...

متن کامل

Quantifying the informativeness for biomedical literature summarization: An itemset mining method

OBJECTIVE Automatic text summarization tools can help users in the biomedical domain to access information efficiently from a large volume of scientific literature and other sources of text documents. In this paper, we propose a summarization method that combines itemset mining and domain knowledge to construct a concept-based model and to extract the main subtopics from an input document. Our ...

متن کامل

Text Summarization by Sentence Segment Extraction Using Machine Learning Algorithms

We present an approach to the design of an automatic text summarizer that generates a summary by extracting sentence segments. First, sentences are broken into segments by special cue markers. Each segment is represented by a set of predeened features (e.g. location of the segment, number of title words in the segment). Then supervised learning algorithms are used to train the summarizer to ext...

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 2015