10 citations · 38 across the 37 of their papers we have counts for
9 papers · 1 filter
An Algorithm for Reducing Approximate Nearest Neighbor to Approximate Near Neighbor with O(logn) Query Time
Hengzhao Ma, Jianzhong Li
This paper proposes a new algorithm for reducing Approximate Nearest Neighbor problem to Approximate Near Neighbor problem. The advantage of this algorithm is that it achieves O(lo…
On the Fairness of Quality-based Data Markets
Dan Zhang, Hongzhi Wang, Xiaoou Ding +3
For data pricing, data quality is a factor that must be considered. To keep the fairness of data market from the aspect of data quality, we proposed a fair data market that conside…
Mining CFD Rules on Big Data
Hongzhi Wang, Mingda Li, Jiawei Zhao +2
Current conditional functional dependencies (CFDs) discovery algorithms always need a well-prepared training data set. This makes them difficult to be applied on large datasets whi…
Schema Integration on Massive Data Sources
Tianbao Lia, Hongzhi Wang, Jianzhong Li +1
As the fundamental phrase of collecting and analyzing data, data integration is used in many applications, such as data cleaning, bioinformatics and pattern recognition. In big dat…
Diversification on Big Data in Query Processing
Meifan Zhang, Hongzhi Wang, Jianzhong Li +1
Recently, in the area of big data, some popular applications such as web search engines and recommendation systems, face the problem to diversify results during query processing. I…
Improve3C: Data Cleaning on Consistency and Completeness with Currency
Xiaoou Ding, Hongzhi Wang, Jiaxuan Su +2
Data quality plays a key role in big data management today. With the explosive growth of data from a variety of sources, the quality of data is faced with multiple problems. Motiva…
MISS: Finding Optimal Sample Sizes for Approximate Analytics
Xuebin Su, Hongzhi Wang, Jianzhong Li +1
Nowadays, sampling-based Approximate Query Processing (AQP) is widely regarded as a promising way to achieve interactivity in big data analytics. To build such an AQP system, findi…
QuickIM: Efficient, Accurate and Robust Influence Maximization Algorithm on Billion-Scale Networks
Rong Zhu, Zhaonian Zou, Yue Han +2
The Influence Maximization (IM) problem aims at finding k seed vertices in a network, starting from which influence can be spread in the network to the maximum extent. In this pape…
Impacts of Dirty Data: and Experimental Evaluation
Zhixin Qi, Hongzhi Wang, Jianzhong Li +1
Data quality issues have attracted widespread attention due to the negative impacts of dirty data on data mining and machine learning results. The relationship between data quality…