J
Jun Long
Researcher at Central South University
Publications - 23
Citations - 756
Jun Long is an academic researcher from Central South University. The author has contributed to research in topics: Computer science & WordNet. The author has an hindex of 7, co-authored 18 publications receiving 501 citations.
Papers
More filters
Journal ArticleDOI
A Lexicon-based Approach for Hate Speech Detection
TL;DR: The goal of the research is to create a model classifier that uses sentiment analysis techniques and in particular subjectivity detection to not only detect that a given sentence is subjective but also to identify and rate the polarity of sentiment expressions.
Journal ArticleDOI
Turning from TF-IDF to TF-IGM for term weighting in text classification
TL;DR: Experimental results show that TF-IGM outperforms the famous TF-IDF and the state-of-the-art supervised term weighting schemes and some new findings different from previous studies are obtained and analyzed in depth in the paper.
Journal ArticleDOI
Fractal Dimension Analysis of Subcortical Gray Matter Structures in Schizophrenia.
Guihu Zhao,Guihu Zhao,Kristina Denisova,Pejman Sehatpour,Pejman Sehatpour,Jun Long,Weihua Gui,Jianping Qiao,Daniel C. Javitt,Daniel C. Javitt,Zhishun Wang +10 more
TL;DR: High-resolution, three-dimensional fractal geometry analysis is used to study subtle and potentially biologically relevant structural alterations in subcortical gray matter (GM) in patients with schizophrenia relative to healthy individuals, providing in-vivo quantitative evidence for reduced surface complexity of hippocampus.
Journal ArticleDOI
Identifying vital nodes from local and global perspectives in complex networks
TL;DR: A Local-and-Global-Centrality (LGC) measuring algorithm to identify the vital nodes through handling local as well as global topological aspects of a network simultaneously is proposed.
Journal ArticleDOI
A fast incremental algorithm for constructing concept lattices
Ligeng Zou,Zuping Zhang,Jun Long +2 more
TL;DR: The algorithm, called FastAddIntent, results as a modification of AddIntent in which it is shown that the number of children of any concept has an upper bound and the procedure of updating the upper neighbors of a new concept is improved.