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Project 28: Delve: A web-based system for data set retrieval and document analysis

Suitable Majors

Computer Engineering, Computer Science, Electrical & Computer Engineering

Research Area

Data Mining, Machine Learning

Internship Description

Delve is a system under developing in my group. It is a web-based system for data set retrieval and document analysis. This system is different from other scholarly search engines as it provides a medium for both data set retrieval and real time visual exploration and analysis of data sets and documents. The system currently supports queries and analysis based on a database including over 2 million academic publications from more than 1000 different conferences and journals.
We need students who can contribute to the system by applying machine learning and data mining techniques on analyzing the document text, citation and co-author graphs.
The methodology will include popular machine learning and data mining techniques such as graph embedding, deep learning, multi-label classification and so on. ​


Students should have learned math courses such as linear algebra, probability and statistics, and also be good at programming e.g., by Java, Python etc. It would be great if students have taken machine learning and data mining courses.


The outcomes are expected to improve our current Delve system by providing more accurate search results.  

Other Comments

​Internship dates: 19 May to 26 July or 23 June to 29 August or 7 July to 14 September​


Computer, Electrical and Mathematical Sciences and Engineering

Faculty Name

Xiangliang Zhang