Text document classification approaches are designed to categorise documents into
predefined classes. These approaches have two main components: document …

Multi-document summarization is the process of extracting salient information from a set of
source texts and present that information to the user in a condensed form. In this paper, we …

In recent years, research in text summarization has become very active for many languages.
Unfortunately, looking at the effort devoted to Arabic text summarization, we find much fewer …

Text summarization is one of the most challenging and difficult tasks in natural language
processing, and artificial intelligence more generally. Various approaches have been …

This system proposes Multi-lingual (Tamil and English) Multi-document summarization by
neural networks. The system involves three steps. In first step, the sentences of the …

目前各個搜尋引擎所產生的網頁摘要, 大多無法提供使用者充足的摘要內容判斷資訊,
更可能造成使用者的誤導. 本研究希望搜尋引擎將查詢結果回傳給使用者時 …

The use of the latent semantic analysis (LSA) in text mining demands large space and time
requirements. This paper proposes a new text extraction method that sets a framework on …

With the abundance of data that can be accessed quickly now, it has become one of the
difficulties for people to find specific information on the web. Many documents are available …

The massive upload of text on the internet makes the text overhead one of the important
challenges faces the Information Retrieval (IR) system. The purpose of this research is to …

In the recent years, with the expansion of the Internet there has been tremendous growth in
the volume of electronic text documents available information on the Web, which making …