temporal recommendation on graphs via long and short-term
DESCRIPTION
TRANSCRIPT
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Temporal recommendation on graphs via long- and short-term preference fusion
Liang [email protected]
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Main Content
• Temporal Recommendation– Long/short term preference
• Bipartite Graph Model– Session Graph Model– Path Fusion Algorithm
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Related Works
• Neighborhood Model [Ding CIKM05]– Users future preference is mainly dependent on
their recent behavior• Latent Factor Model [Koren KDD09]– User bias shifting– Item bias shifting– User preference shifting– Seasonal effects
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Our Contribution
• Temporal Recommendation on Graph Model– Implicit feedback data
• Combine Long/short term interest together
Graph Model Temporal Recommendation
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Long/Short Term Preference
Short-term PreferenceLong-term Preference
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Long/Short Term Preference
• Long term preference– Personal preference– Do not change frequently– Last for long period
• Short term preference– Influenced by social event– Change frequently– May be become long term preference
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Session Graph Model
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Session Graph Model
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(A,a,1) (A,c,2)(B,b,1) (B,c,2)
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Bipartite Graph Model Session Graph Model
Session Node
User Node
Item Node
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Session Graph Model
Session Node
User Node
Item Node
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Ranking and Recommendation
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Path Fusion Ranking
• Two nodes in a graph have large similarity if:– There are many paths between two nodes;– These paths have short length;– Most of these paths do not contains nodes with
large out degree.
[YouTube WWW2008]
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Path Fusion Ranking
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( ) ( , )( )
| ( ) |
Ni i i
i i
v w v vweight P
out v
( , ')
( , ') ( )P path v v
d v v weight P
( ) ( , ) ( ) ( , ) ( ) ( , )( , , , )
| 2 | | 2 | | 2 |
A w A c c w c B B w B bweight A c B b
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Path Fusion Ranking1. Implement by Breath-First-Search2. Fast and low space complexity
a) Its speed dependents on graph sparsity;
b) It can be speed up by randomly select edges;
c) Do not need to store user-user or item-item similarity matrix
3. Easy to do incremental updatea) New data can insert into graph
directly;b) After graph is updated,
recommendation result will be changed immediately
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Experiments
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Experiments
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Experiments
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This model does not work in every system!
Future work
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Temporal Effectiveness
Slow Evolution SystemSession Graph Model Perform Good
Fast Evolution SystemSession Graph Model Perform Bad
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Temporal Effectiveness
0 10 20 30 40 50 600
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nytimes youtube wikipediasourceforge blogspot netflix
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Solution
• Add Item Session Node
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B:1
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a:1
b:1
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(A,a,1) (A,c,2)(B,b,1) (B,c,2)