information filtering on dynamical networks associate prof. jianguo liu
DESCRIPTION
Information filtering on dynamical networks Associate Prof. Jianguo Liu University of Shanghai for Science and Technology 2010-8-13 E-mail:[email protected]. Outline. Why recommendation systems are needed? How to recommend new information? Some proposed works. Conclusion and discussions. - PowerPoint PPT PresentationTRANSCRIPT
© Business School, 2010
Information filtering on dynamical networks
Associate Prof. Jianguo LiuUniversity of Shanghai for Science and Technology
2010-8-13
E-mail:[email protected]
© Business School, 2010
Outline
1. Why recommendation systems are needed?
2. How to recommend new information?
3. Some proposed works.
4. Conclusion and discussions
© Business School, 2010
Our Group
University of Shanghai for Science and Technology Prof. Yi-Cheng Zhang, Jian-Gu
o Liu, Qiang Guo University of Fribourg
Prof. Yi-Cheng Zhang, Medo Matus, Zico, Linyuan, Cihang
University of Science and Technology of China Prof. Bing-Hong Wang
University of Electronic Science and Technology of China Prof. Tao Zhou, Ming-Sheng Sh
ang, Le Dong
© Business School, 2010
1.Why recommend?
Facebook CEO
© Business School, 2010
Why recommend
We face too much data and sources to be able to find out those most relevant for us. Indeed, we have to make choices from thousands of movies, millions of books, billions of web pages, and so on. Evaluating all these alternatives by ourselves is not feasible at all.As a consequence, an urgent problem is how to automatically find out the relevant objects for us.
© Business School, 2010
2. Recommendation algorithms
1. Collaborative filtering algorithm
2. Content-based algorithm
3. Struture-based algorithms
© Business School, 2010
2.1Collaborative filtering algorithm
Herlocker et al., ACM Trans. Inf. Syst. 22: 5-53 (2004)
© Business School, 2010
The user will be recommended items similar to the ones this user preferred in the past
Pazzani & Billsus, LNCS 4321: 325-341 (2007)
2.2Content-based algorithm
© Business School, 2010
2.3 Structure-based algorithms
© Business School, 2010
3. Hybrid algorithm
T. Zhou, Z. Kuscisik, JG Liu, M. Medo, JR Wakeling, YC Zhang, PNAS 107(10) 4511 (2010) .
Heat conduction
Mass diffusion
© Business School, 2010
Hybrid algorithm
© Business School, 2010
3.2 Information filtering on weighted user-object bipartite networks
© Business School, 2010
© Business School, 2010
© Business School, 2010
4. Conclusion and discussions
What’s the meaning of the edge weight possion distribution？
How to design the efficient dynamic algorithm；What’s the relationship between the statistical pro
perties of the data and the recommendation performance?
How to construct the mathematical model?The evolution model based on the link prediction
mechanism.
© Business School, 2010
Thanks to NSFC(10905052,70901010), and Shanghai Leading Discipline Project (No. S30501).
© Business School, 2010
Many thanks!!