Dissertation Data Mining

Dissertation Data Mining-46
“Even during weekend nights, (Han) spent hours remotely to give me advice on my research projects and plans, and to teach me how to do research, write scientific papers and manage all sorts of things in my Ph D Career,” Ren said.

“Even during weekend nights, (Han) spent hours remotely to give me advice on my research projects and plans, and to teach me how to do research, write scientific papers and manage all sorts of things in my Ph D Career,” Ren said.

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The applications of this research are far reaching for the fields of data mining, information retrieval, profiling and demographic inference, online advertising and fraud detection.

Perozzi, whose advisor was Stony Brook Professor Steven Skiena, defended his thesis in May 2016.

The flood of online information now being produced has provided a rich environment for data mining and discovery, but that near-endless flow of text is difficult to make sense of.

As an Illinois Computer Science Ph D student, Xiang Ren devoted his work to finding better ways to sort and categorize that jumble of text, and his dissertation was recognized this month with the 2018 SIGKDD Doctoral Dissertation Award.

The annual award acknowledges excellent doctoral research in the field of data mining and knowledge discovery.

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Bryan Perozzi and Steven Skiena Perozzi thesis, , was recognized as the best dissertation of the year in the data science community.

Note: Some theses and dissertations may be embargoed up to a year after graduation before public release; please see the Graduate School Information.

Copyright of the original thesis is retained by the author.

“Xiang did brilliant work during his Ph D study and his work has been well cited and well recognized,” Han said.

Ren called studying under Han “an amazing experience” that prepared him for an academic career by including him in grant-proposal writing, paper reviewing, principal investigator meetings, and guest lectures.

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