Regarding GSoC 2019 "Clickstream Mining for Learning to Rank"

[Cong Ding]

Hi, everyone!

I'm Cong Ding, a second year undergraduate student from Peking University, Beijing(UTC +0800). I am interested in the project "Clickstream Mining for LeToR" for this year's GSoC. 

I have already taken the courses of basic math(calculus, linear algebra, probability and statistics & discrete mathematics), programming and computer system. Since January I have been working on an open source graph database system called gStore(written in C++) in Data Management Lab, and my work is to optimize the index structure, so I am familiar with C++ project. Also I'm taking a course in Python and data mining this semester. 

Honestly, I haven't used Xapian before. But I have been working on the project these days. I followed the GSoC guide of Xapian and read the papers listed on the website. You can see my learning notes on my blog(https://congding.info/blog/) and now I have a simple view of click models. I found myself more interested in the project as I went in deeper research. In fact, the work on this project have enlightened me to apply click model to my course project. BTW, I'm a new blogger and wish to develop the habit of blogging. I will try to keep updating this blog. :)

Besides, I browsed the previous GSoC 2017 project and looked into the relevant code. I'm now trying to implement MLE algorithm for the SDBN click model. I hope to complete my first version before Friday. For future work, if we want to implement other click models, I believe a test algorithm to compare the performance of different models is important. As for end-to-end use of LeToR with Omega, I haven't got a clue yet. Hope to discuss with you!

After implementing the MLE algorithm, I will focus on my GSoC proposal. Looking forward to coding with you this summer!

Cheers, 
Cong Ding 
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Peking University 
Computer Science and Technology 
E-mail: congding at pku.edu.cn 
Mobile: +8615810029293 
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