Now I am a visiting scholar co-advised by Chen Li at Department of Information and Computer Science, UC, Irvine since Sep. 2018. I am currently a PhD student advised by X. Sean Wang at Computer Science, Fudan University since Sep. 2014. Before that, I received my bachelor's degree in Information Science and Engineering, Lanzhou University in July, 2014.
My research interests include large scale text data analysis, exploratory data analysis, database system
My CV is here.
GPA: 3.566/4
GPA: 4.77/5
Undergraduate Thesis: Chem2Dot: a CML to Chemical Braille Translation Software (Excellent Undergraduate Thesis)
Zhihui Yang, Jiyang Gong, et al. iExplore: Accelerating Exploratory Data Analysis by Predicting User Intention[C]International Conference on Database Systems for Advanced Applications (DASFAA). Springer, Cham, 2018: 149-165.
Zhihui Yang, Huixin Ma, et al. Finding maximal ranges with unique topics in a text database[J]. World Wide Web, 2018, 21(2): 289-310.
Huixin Ma, Zhihui Yang, et al. Answering unique topic queries with dynamic threshold[J]. World Wide Web, 2018: 1-20.
Kaiwen Zhou, Zhihui Yang, et al. Design and development of partitional topic model. Journal of Frontiers of Computer Science and Technology, 2017. doi:10.3778/j.issn.1673-9418
Lvhong Liu, Zhihui Yang, et al. Unique topic query system based on relational information extraction. In The 34th national database conference, 2017.
Lvhong Liu, Zhihui Yang, et al. Unique topic query processing on cloud. IEEE International Conference on Cyber Security and Cloud Computing, 2018
We introduced the concept of unique topics to discover topics that appear frequently within a small range of documents in contrast to the whole range.
We also proposed a pruning-based optimization (PBO) algorithm to find the maximal ranges of the specified unique topic. The PBO algorithm reduced the time complexity from O(n^3) to O(n^2). Additionally, we further reduced the time complexity to O(n).
Based on LDA, we developed a new topic model DbLDA to utilize the commonalities inside each subset in a text database.
These works was published on WWWJ2017 and WWWJ2018
Hubble: A Smart System for Data Exploration in Big Data Era, bridge the gap between analysts and data
iExplore: Accelerating Exploratory Data Analysis by Predicting User Intention. (i)We introduced an intention model to help the iExplore system have a comprehensive understanding of user’s intention. (ii)We also studied the convergence of the intention model to figure out the characteristic of the exploratory process.
This work was published on DASFAA2018
We designed a method to translate Chemical Markup Language (CML) to Braille to facilitate information accessibility.
Thisworkwas funded by Hui-Chun Chin and Tsung-Dao Lee ChineseUndergraduate Research Endowment, CURE.
My undergraduate thesis about this work was awarded Excellent Undergraduate Thesis.
Gallery contains some pictures taken by me.