In natural language processing, short-text semantic similarity (STSS) is a very prominent
field. It has a significant impact on a broad range of applications, such as question …

Natural Language Processing (NLP) is the computerized approach to analyzing text using
both structured and unstructured data. NLP is a simple, empirically powerful, and reliable …

Pathology reports contain the essential data for both clinical and research purposes.
However, the extraction of meaningful, qualitative data from the original document is difficult …

The extraction of keywords is a critical task in natural language processing and information
retrieval. It has become increasingly important in a wide range of applications, from search …

For large amount of patent texts, how to extract their keywords in an unsupervised way is a
very important problem. In existing methods, only the own information of patent texts is …

The e-government platform not only enables the government department to publish policy
texts online, but also makes it easier for users to access the policy, especially for the …

For short text classification, insufficient labeled data, data sparsity, and imbalanced
classification have become three major challenges. For this, we proposed multiple weak …

Keyword extraction is an important topic applicable to a wide range of areas such as span
detection, information classification, sentiment analysis, and so on. There are hundreds of …

Automatic keywords extraction is a method that extracts words or phrases from a document
which can express the main idea of the document. In this paper, we propose an …

Domain-specific keyword extraction is a vital task in the field of text mining. There are
various research tasks, such as spam e-mail classification, abusive language detection …