The problem of query-focused multi-document summarization (QMDS) is to generate a
summary from multiple source documents on identical/similar topics based on the query …

Examination assessments undertaken by educational institutions are pivotal since it is one
of the fundamental steps to determining students' understanding and achievements for a …

Multi-document summarization (MDS) is a topic of much attention in extensive knowledge
areas. Extractive MDS techniques intend to shrink the text from a document compilation by …

Managing emergency events, such as natural disasters, requires management teams to
have an up-to-date view of what is happening throughout the event. In this paper, we …

With the acceleration of globalization, machine translation (MT) plays an increasingly
prominent role in cross-language communication. However, how to evaluate the quality of …

Due to the exponential increase in the information on the web, extracting relevant
documents for users in a reasonable time becomes a cumbersome task. Also, when user …

Multi-document summarization (MDS) is an automated process designed to extract
information from various texts that have been written regarding the same subject. Here, we …

Abstract Machine reading comprehension is introduced to improve machines' readability
and understandability of human languages. This sophisticated version of natural language …

Comparative Graph-based Summarization of Scientific Papers Guided by Comparative
Citations Page 1 Comparative Graph-based Summarization of Scientific Papers Guided by …

Query-Focused Multi-Document Summarization (QF-MDS) is the task of automatically
generating a summary from a collection of documents that answers a specific user's query …