Difference between revisions of "Shmueli et. al. WWW2012"
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| + | The author established two data sets: News Vine and Yahoo! For News Vine, the author crawled all the articles from May to September 2011, including all the tags and all the associated comments. They also crawled the friends relationships from for each commender. | ||
| − | The | + | And the Yahoo! data sets are constructed following the same way. |
| + | == Approaches == | ||
| + | |||
| + | 1.Memory Based Approach. | ||
| + | The authors defined a co-occurrence similarity function as follows: | ||
Revision as of 01:09, 2 October 2012
Contents
Citation
E Shmueli, A Kagian, Y Koren, R Lempel Care to Comment? Recommendations for Commenting on News Stories WWW2012
Summary
In this paper, the authors address the following problem, "How to recommend News Stories to recommend?"
They treat this problem as a classic recommendation problem. They use two approaches to recommend article to users. Memory based approach and Latent Factor Model.
Datasets
The author established two data sets: News Vine and Yahoo! For News Vine, the author crawled all the articles from May to September 2011, including all the tags and all the associated comments. They also crawled the friends relationships from for each commender.
And the Yahoo! data sets are constructed following the same way.
Approaches
1.Memory Based Approach. The authors defined a co-occurrence similarity function as follows:
