The enormous increase in digital scholarly data and computing power combined with recent advances in text mining, linguistics, network science, and scientometrics make it possible...
—A major assumption in many machine learning and data mining algorithms is that the training and future data must be in the same feature space and have the same distribution. How...
The frequent items problem is to process a stream of items and find all items occurring more than a given fraction of the time. It is one of the most heavily studied problems in d...
Although many algorithms have been developed to harvest lexical resources, few organize the mined terms into taxonomies. We propose (1) a semi-supervised algorithm that uses a roo...
In this paper, given a set of research papers with only title and author information, a mining strategy is proposed to discover and organize the communities of authors according to...