In the rapidly evolving field of natural language processing, the demand for efficient
automated text summarization systems that not only distill extensive documents but also …

Purpose Learning from safety accidents and sharing safety knowledge has become an
important part of accident prevention and improving construction safety management …

In the field of text summarization, extractive techniques aim to extract key sentences from a
document to form a summary. However, traditional methods are not sensitive enough to …

Background and Objectives: Text summarization plays an essential role in reducing time
and cost in many domains such as medicine, engineering, etc. On the other hand, manual …

Abstract Multi-Document Summarization (MDS) is a challenging task due to the fact that
multiple documents not only have extremely long inputs but may also be overlap** …

Automatic text summarization is one of the most promising solutions to the ever-growing
challenges of textual data as it produces a shorter version of the original document with …

Collaborative creativity (cocreativity) is essential to generate original solutions for complex
challenges faced in organisations. Effective cocreativity requires the orchestration of …

Extractive query-focused multi-document summarization (QF-MDS) is the process of
automatically generating an informative summary from a collection of documents that …

Content curation is a significant step to identify the relevant content for the searched topics.
There are many methods introduced to generate summarized contents but those methods …

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 …