Zonglin TianUtrecht University | UU · Department of Information and Computing Sciences
Zonglin Tian
Doctor of Philosophy
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About
15
Publications
3,657
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127
Citations
Introduction
DR Method, Explainable Projections.
Additional affiliations
September 2016 - June 2019
Education
November 2019 - October 2023
Publications
Publications (15)
How to classify and organize the semantic Web services to help users find the services to meet their needs quickly and accurately is a key issue to be solved in the era of service-oriented software engineering. This paper makes full use the characteristics of solid mathematical foundation and stable classification efficiency of naive bayes classifi...
How to recommend the atomic and a set of services with correlations to meet users’ functional and non-functional requests is a key problem to be solved in the era of services computing. On the basis of organizing service clusters with different functions using the three-stage Bayesian network structure learning method. It uses the parameter learnin...
How to mine the gene regulatory relationship and construct gene regulatory network (GRN) is of utmost interest within the whole biological community, however, which has been consistently a challenging problem since the tremendous complexity in cellular systems. In present work, we construct gene regulatory network using an improved three-phase depe...
Multidimensional projections (MPs) are effective methods for visualizing high-dimensional datasets to find structures in the data like groups of similar points and outliers. The insights obtained from MPs can be amplified by complementing these techniques by several so-called explanatory mechanisms. We present and discuss a set of six such mechanis...
Projections are well-known techniques that help the visual exploration of high-dimensional data by creating depictions thereof in a low-dimensional space. While projections that target the 2D space have been studied in detail both quantitatively and qualitatively, 3D projections are far less well understood, with authors arguing both for and agains...
Multidimensional projections (MPs) are established tools for exploring the structure of high-dimensional datasets to reveal groups of similar observations. For optimal usage, MPs can be augmented with mechanisms that explain what such points have in common that makes them similar. We extend the set of such explanatory instruments by two new techniq...
Background and Objective
Mining the genes related to maize carotenoid components is important to improve the carotenoid content and the quality of maize.
Methods
On the basis of using the entropy estimation method with Gaussian kernel probability density estimator, we use the three-phase dependency analysis (TPDA) Bayesian network structure learni...
The experiment data 1 of 109 nodes, the experiment data 2 of 109 nodes, and so on are shown here.
MODEM is a comprehensive database of maize multidimensional omics data, including genomic, transcriptomic, metabolic and phenotypic information from the cellular to individual plant level. This initial release contains approximately 1.06 M high quality SNPs for 508 diverse inbred lines obtained by combining variations from RNA sequencing on whole k...
With the development of web service applications, how to improve the efficiency of service discovery is an important research work in service computing era. Based on the service clusters which are formed through service clustering, this paper uses the Decorator Pattern ideology to organize the service clusters according to the collaborative relatio...
In the era of service computing, it needs to develop web service aggregation platform to organize and manage services, and thus to help users to discover the atomic and a set of services with correlations to meet their functional and non-functional requirements. This is an important research point in the service-oriented software engineering. This...
Questions
Questions (2)
I was going to find several title formats, but interestingly, I found that these two title structures already cover most papers.I know that research papers must emphasize the method they used, but I want to know if we can use English grammar to create a more unique and attractive title for our papers?
Some common formats:
a + : + b
- a is noun phrase
- b is the description of a
a + prep + b
- a is do(ing) something
- b is some techniques
- prep is with, by, in, of, on, for...
Welcome to list the interesting titles you've seen : )
For large social networks, such as tens of millions of nodes and hundreds of millions of edges, traditional visualization techniques are obviously unable to handle, even with some decoration techniques (such as graphics substitution, edge bundling), the amount of computation is enormous.
Assuming a scenario: Now that you have 50 gigabytes of graph data (probably in a side table format), can we design a system to explore the content of this 50 Gigabyte data (such as structure, aggregation)?
Note:
Obviously, even if the result is not analyzed, the above system should at least display the data. However, even simple display is very difficult in this case. So, maybe we need to use these big data tools, such as Spark,especially I think the GraphX maybe used.
As for the above, I often wonder, for the visualization of large scale data, if this still belongs to the purely visualization field. Should we focus on data processing? Should we focus on building distributed computing models? Should we focus on optimizing the computing framework?
If we should, then for the research that has good results. How to highlight the original visual theme? For others, without good results, how do we determine whether the bad results are due to problems with visual processes or distributed frameworks?
Introducing a framework like spark assumes that more variables need to be adjusted, actually it perhaps makes the process more complex, we need to consider more details of the distributed framework, which is, I think, a disaster for the original visualization process!
What do you think of the above content ?
I would be very grateful if you give your opinion.
