As text semantics has an important role in text meaning, the term semantics has been seen
in a vast sort of text mining studies. However, there is a lack of studies that integrate the …

Accurate semantic representation models are essential in text mining applications. For a
successful application of the text mining process, the text representation adopted must keep …

Since the last two decades, XML has gained momentum as the standard for web information
management and complex data representation. Also, collaboratively built semi-structured …

Understanding the rapidly growing short text is very important. Short text is different from
traditional documents in its shortness and sparsity, which hinders the application of …

The rapid growth of online social media in the form of collaborativelycreated content
presents new opportunities and challenges to both producers and consumers of information …

With the rapid growth of social Web applications such as Twitter and online advertisements,
the task of understanding short texts is becoming more and more important. Most traditional …

Most text mining tasks, including clustering and topic detection, are based on statistical
methods that treat text as bags of words. Semantics in the text is largely ignored in the …

Short text clustering is a challenging problem when adopting traditional bag-of-words or TF-
IDF representations, since these lead to sparse vector representations of the short texts. Low …

Recent years have seen a great deal of work that exploits collaborative, semi-structured
content for Artificial Intelligence (AI) and Natural Language Processing (NLP). This special …

Determining the number of clusters is an important part of cluster validity that has been
widely studied in cluster analysis. Sum-of-squares based indices show promising properties …