Enormous amount of online information, available in legal domain, has made legal text
processing an important area of research. In this paper, we attempt to survey different text …

The massive quantity of data available today in the Internet has reached such a huge
volume that it has become humanly unfeasible to efficiently sieve useful information from it …

Transductive classification is a useful way to classify texts when labeled training examples
are insufficient. Several algorithms to perform transductive classification considering text …

Manual summarization of large documents of texts is tedious and error prone. Also, the
results in such kind of summarization may lead to different results for a particular document …

This paper details the features and the methodology adopted in the construction of the CNN-
corpus, a test corpus for single document extractive text summarization of news articles. The …

Text summarization is to generate a condensed version of the original document. The major
issues for text summarization are eliminating redundant information, identifying important …

The essence of extractive summarization is to measure the importance of sentences in the
document. When extracting summary from a single document, it is difficult to …

With the rapid development of we‐media information dissemination, WeChat official
accounts platform has become an important way for people to obtain health related …

Abstract Summary is the meaningful concise version of a text document. Generally existing
statistical, knowledge based and discourse based extractive summarization methods use …

As a typical unsupervised learning method, the TextRank algorithm performs well for large-
scale text mining, especially for automatic summarization or keyword extraction. However …