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Publication search results
found 24 matches
- 2019
- Balsam Alkouz, Zaher Al Aghbari, Jemal H. Abawajy:
Tweetluenza: Predicting flu trends from twitter data. Big Data Min. Anal. 2(4): 273-287 (2019) - Mondher Bouazizi, Tomoaki Ohtsuki:
Multi-class sentiment analysis on twitter: Classification performance and challenges. Big Data Min. Anal. 2(3): 181-194 (2019) - Zengqiang Fang, Xiujuan Lei:
Prediction of miRNA-circRNA associations based on k-NN multi-label with random walk restart on a heterogeneous network. Big Data Min. Anal. 2(4): 261-272 (2019) - Wentao Han, Kaiwei Li, Shimin Chen, Wenguang Chen:
Auxo: a temporal graph management system. Big Data Min. Anal. 2(1): 58-71 (2019) - Jing (Selena) He, Meng Han, Shouling Ji, Tianyu Du, Zhao Li:
Spreading social influence with both positive and negative opinions in online networks. Big Data Min. Anal. 2(2): 100-117 (2019) - Bismita Jena, Cynthia Khan, Rajshekhar Sunderraman:
High performance frequent subgraph mining on transaction datasets: A survey and performance comparison. Big Data Min. Anal. 2(3): 159-180 (2019) - Chenguang Kong, Guangchun Luo, Ling Tian, Xiaojun Cao:
Disseminating authorized content via data analysis in opportunistic social networks. Big Data Min. Anal. 2(1): 12-24 (2019) - Sunil Kumar, Maninder Singh:
Big data analytics for healthcare industry: impact, applications, and tools. Big Data Min. Anal. 2(1): 48-57 (2019) - Sunil Kumar, Maninder Singh:
A novel clustering technique for efficient clustering of big data in Hadoop Ecosystem. Big Data Min. Anal. 2(4): 240-247 (2019) - Bing Liu, Shishi Feng, Xuan Guo, Jing Zhang:
Bayesian analysis of complex mutations in HBV, HCV, and HIV studies. Big Data Min. Anal. 2(3): 145-158 (2019) - Jingshu Liu, Li Wang, Jinglei Liu:
Efficient preference clustering via random fourier features. Big Data Min. Anal. 2(3): 195-204 (2019) - Wanling Liu, Weikun Wu, Yingming Wang, Yanggeng Fu, Yanqing Lin:
Selective ensemble learning method for belief-rule-base classification system based on PAES. Big Data Min. Anal. 2(4): 306-318 (2019) - Thosini Bamunu Mudiyanselage, Yanqing Zhang:
Feature selection with graph mining technology. Big Data Min. Anal. 2(2): 73-82 (2019) - Tathagata Mukherjee, Piyush Kumar, Debdeep Pati, Erik Blasch, Eduardo Pasiliao, Liqin Xu:
LoSI: Large scale location inference through FM signal integration and estimation. Big Data Min. Anal. 2(4): 319-348 (2019) - Qi Rao, Yan Yang, Yongquan Jiang:
Condition recognition of high-speed train bogie based on multi-view kernel FCM. Big Data Min. Anal. 2(1): 1-11 (2019) - Chenfei Sun, Qingzhong Li, Lizhen Cui, Hui Li, Yuliang Shi:
Heterogeneous network-based chronic disease progression mining. Big Data Min. Anal. 2(1): 25-34 (2019) - Yaojing Wang, Yuan Yao, Hanghang Tong, Feng Xu, Jian Lu:
A Brief Review of Network Embedding. Big Data Min. Anal. 2(1): 35-47 (2019) - Haiqin Weng, Binbin Zhao, Shouling Ji, Jianhai Chen, Ting Wang, Qinming He, Raheem Beyah:
Towards understanding the security of modern image captchas and underground captcha-solving services. Big Data Min. Anal. 2(2): 118-144 (2019) - Wenmao Wu, Zhizhou Yu, Jieyue He:
A semi-supervised deep network embedding approach based on the neighborhood structure. Big Data Min. Anal. 2(3): 205-216 (2019) - Yumeng Yan, Sheng-You Huang:
A non-redundant benchmark for symmetric protein docking. Big Data Min. Anal. 2(2): 92-99 (2019) - Zhonglin Ye, Haixing Zhao, Ke Zhang, Zhaoyang Wang, Yu Zhu:
Network representation based on the joint learning of three feature views. Big Data Min. Anal. 2(4): 248-260 (2019) - Ying Yu, Min Li, Liangliang Liu, Yaohang Li, Jianxin Wang:
Clinical big data and deep learning: Applications, challenges, and future outlooks. Big Data Min. Anal. 2(4): 288-305 (2019) - Jiangcheng Zhu, Shuang Hu, Rossella Arcucci, Chao Xu, Jihong Zhu, Yike Guo:
Model error correction in data assimilation by integrating neural networks. Big Data Min. Anal. 2(2): 83-91 (2019) - Qile Zhu, Xiyao Ma, Xiaolin Li:
Statistical learning for semantic parsing: A survey. Big Data Min. Anal. 2(4): 217-239 (2019)
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