10 citations · 38 across the 37 of their papers we have counts for
37 papers
Sublinear-time Reductions for Big Data Computing
Xiangyu Gao, Jianzhong Li, Dongjing Miao
With the rapid popularization of big data, the dichotomy between tractable and intractable problems in big data computing has been shifted. Sublinear time, rather than polynomial t…
Rank-Regret Minimization
Xingxing Xiao, Jianzhong Li
Multi-criteria decision-making often requires finding a small representative set from the database. A recently proposed method is the regret minimization set (RMS) query. RMS retur…
The PCP-like Theorem for Sub-linear Time Inapproximability
Hengzhao Ma, Jianzhong Li
In this paper we propose the PCP-like theorem for sub-linear time inapproximability. Abboud et al. have devised the distributed PCP framework for proving sub-quadratic time inappro…
Sublinear Time Nearest Neighbor Search over Generalized Weighted Manhattan Distance
Huan Hu, Jianzhong Li
Nearest Neighbor Search (NNS) over generalized weighted distances is fundamental to a wide range of applications. The problem of NNS over the generalized weighted square Euclidean…
Efficient Approximate Nearest Neighbor Search for Multiple Weighted Distance Functions
Huan Hu, Jianzhong Li
Nearest neighbor search is fundamental to a wide range of applications. Since the exact nearest neighbor search suffers from the "curse of dimensionality", approximate approaches,…
PCP Theorems, SETH and More: Towards Proving Sub-linear Time Inapproximability
Hengzhao Ma, Jianzhong Li
In this paper we propose the PCP-like theorem for sub-linear time inapproximability. Abboud et al. have devised the distributed PCP framework for sub-quadratic time inapproximabili…
Dynamic Approximate Maximum Independent Set on Massive Graphs
Xiangyu Gao, Jianzhong Li, Dongjing Miao
Computing a maximum independent set (MaxIS) is a fundamental NP-hard problem in graph theory, which has important applications in a wide spectrum of fields. Since graphs in many ap…
A Sub-linear Time Algorithm for Approximating k-Nearest-Neighbor with Full Quality Guarantee
Hengzhao Ma, Jianzhong Li
In this paper we propose an algorithm for the approximate k-Nearest-Neighbors problem. According to the existing researches, there are two kinds of approximation criterion. One is…
Sampling Based Approximate Skyline Calculation on Big Data
Xingxing Xiao, Jianzhong Li
The existing algorithms for processing skyline queries cannot adapt to big data. This paper proposes two approximate skyline algorithms based on sampling. The first algorithm obtai…
Efficient Trajectory Compression and Range Query Processing
Hongbo Yin, Hong Gao, Binghao Wang +2
Nowadays, there are ubiquitousness of GPS sensors in various devices collecting, transmitting and storing tremendous trajectory data. However, such an unprecedented scale of GPS da…
Complexity and Efficient Algorithms for Data Inconsistency Evaluating and Repairing
Dongjing Miao, Zhipeng Cai, Jianzhong Li +2
Data inconsistency evaluating and repairing are major concerns in data quality management. As the basic computing task, optimal subset repair is not only applied for cost estimatio…
Auto-Model: Utilizing Research Papers and HPO Techniques to Deal with the CASH problem
Chunnan Wang, Hongzhi Wang, Tianyu Mu +2
In many fields, a mass of algorithms with completely different hyperparameters have been developed to address the same type of problems. Choosing the algorithm and hyperparameter s…
Recognizing the Tractability in Big Data Computing
Xiangyu Gao, Jianzhong Li, Dongjing Miao +1
Due to the limitation on computational power of existing computers, the polynomial time does not works for identifying the tractable problems in big data computing. This paper adop…
Autoregressive-Model-Based Methods for Online Time Series Prediction with Missing Values: an Experimental Evaluation
Xi Chen, Hongzhi Wang, Yanjie Wei +2
Time series prediction with missing values is an important problem of time series analysis since complete data is usually hard to obtain in many real-world applications. To model t…
A True Algorithm for the All-k-Nearest-Neighbors Problem
Hengzhao Ma, Jianzhong Li
In this paper we examined an algorithm for the All-k-Nearest-Neighbor problem proposed in 1980s, which was claimed to have an upper bound on the running time. We find…
Regular Expression Matching on billion-nodes Graphs
Hongzhi Wang, Jiabao Han, Bin Shao +1
In many applications, it is necessary to retrieve pairs of vertices with the path between them satisfying certain constraints, since regular expression is a powerful tool to descri…
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…