Semantic Data Mining refers to the data mining tasks that systematically incorporate domain
knowledge, especially formal semantics, into the process. In the past, many research efforts …

The number of online documents has rapidly grown, and with the expansion of the Web,
document analysis, or text analysis, has become an essential task for preparing, storing …

Numerous number of tourism attractions along with a huge amount of information about
them on web and social platforms have made the decision-making process for selecting and …

Short text clustering is a challenging problem due to its sparseness of text representation.
Here we propose a flexible Self-Taught Convolutional neural network framework for Short …

Traditional clustering algorithms do not consider the semantic relationships among words so
that cannot accurately represent the meaning of documents. To overcome this problem …

Short text clustering has become an increasing important task with the popularity of social
media, and it is a challenging problem due to its sparseness of text representation. In this …

Background Internet provides different tools for communicating with patients, such as social
media (eg, Twitter) and email platforms. These platforms provided new data sources to shed …

Exponential growth of biomedical literature and clinical data demands more robust yet
precise computational methodologies to extract useful insights from biomedical literature …

Data mining is the discovery of meaningful information or unrevealed patterns in data.
Traditional data‐mining approaches, using statistical calculations, machine learning …

Clustering is a branch of data mining which involves grouping similar data in a collection
known as cluster. Clustering can be used in many fields, one of the important applications is …