Abstract. Multiple document summarization is becoming increasingly important as a way of reducing information overload, particularly in the context.
Identifying Information Units for Multiple Document Summarization. Seamus Lyons, Dan Smith. 2005. Abstract. Multiple document summarization is becoming ...
Mar 23, 2017 · 1 Introduction. In this paper we address the problem of producing a comprehensive summary from a. set of documents describing an event, none of ...
In this paper, we propose a new task of summarizing diverse information encountered in multiple news articles encompassing the same event.
This paper proposes an extraction-based model which uses graph- based and information theoretic concepts for multi- document summarization. Our method ...
In a document set, the specific representation learner aims to identify the specific information within each document. To achieve this, we introduce a ...
Automatic summarizers typically identify and extract the most important sentences from an input article. A variety of approaches exist for determining the ...
People also ask
What are the techniques of multi-document summarization?
What is the difference between multi-document summarization and single document summarization?
What is multiple document text summarization in NLP?
What is single document summarization?
BEs are intended to represent the high-informative unigrams, bigrams, and longer units of a text, which can be built up composi- tionally. An important ...
This paper addresses the issue of overly general content generation by common multi-document summarization models and proposes a topic-oriented multi-document ...
Feb 2, 2023 · Automatic text summarization (ATS) becomes an important way of finding relevant information precisely in large text in a short time with ...