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From Manuel Blechschmidt <Manuel.Blechschm...@gmx.de>
Subject Re: Time-based preferences for recommendation
Date Tue, 29 Nov 2011 14:50:10 GMT
Hi Ted,
I agree with you. I would love to release it.

Unfortunately it is not my data therefore I can not just release it to public not even anonymized.
If someone is willing to contribute new algorithms I can release anonymized data sets on a
personal basis.

The problem is that there are quite reliable ways to deanonymize data in a reliable way [1].
Further this is also used [2].

Germany is a lot more restricted about privacy laws.

So if someone is interested in using my dataset send me an email.

/Manuel

[1] Narayanan, Arvind ; Shmatikov, Vitaly: Robust De-anonymization of Large Sparse Datasets.
In: Proceedings of the 2008 IEEE Symposium on Security and Privacy. Washington, DC, USA :
IEEE Computer Society, 2008. – ISBN 978–0– 7695–3168–7, 111–125
[2] Barbaro, Michael ; Jr., Tom Z.: A Face Is Exposed for AOL Searcher No. 4417749. http://www.nytimes.com/2006/08/09/technology/09aol.html?_r=1.
Version: August 2006, Checked: 2011-03-09
[3] http://www.wired.com/threatlevel/2009/12/netflix-privacy-lawsuit/


On 29.11.2011, at 15:31, Ted Dunning wrote:

> Manuel,
> 
> If you can blind your data sufficiently to release it publicly, it would
> make it much easier to get others to help with this.
> 
> On Tue, Nov 29, 2011 at 3:21 AM, Manuel Blechschmidt <
> Manuel.Blechschmidt@gmx.de> wrote:
> 
>> Hello Anatoliy,
>> 
>> On 29.11.2011, at 10:32, Anatoliy Kats wrote:
>> 
>>> Hi,
>>> 
>>> There was a conversation some time ago about incorporating time
>> dependency for preferences:
>> http://thread.gmane.org/gmane.comp.apache.mahout.user/2951
>>> 
>>> Has there been any more discussion about this?  Has anything been
>> checked into Mahout?  Is anyone working on it?  I might be able to pitch in.
>> 
>> 
>> I am currently working with a data set which has highly seasonal data.
>> Actually it is the sales data of a merchant selling tea and spices.
>> 
>> I benchmarked the different recommenders against it:
>> http://thread.gmane.org/gmane.comp.apache.mahout.user/10433
>> 
>> As far as I know there are currently no recommenders that incorporate time
>> or seasons. The DataModel supports it but it isn't used.
>> 
>> I would guess that identifying seasonal patterns could enhance my
>> recommendations a lot.
>> 
>> I scanned the following paper:
>> Improving E-Commerce Recommender Systems by the Identification of Seasonal
>> Products
>> http://www.aaai.org/Papers/Workshops/2007/WS-07-08/WS07-08-011.pdf
>> 
>> Actually I think that what the paper is doing is not that advanced.
>> 
>> I currently try to identify seasonal products with R. I am playing around
>> with seasonal ARIMA models (http://www.duke.edu/~rnau/seasarim.htm
>> http://cran.r-project.org/web/packages/forecast/forecast.pdf). If I have
>> a working solution with R I might implement it in Mahout.
>> 
>> What is your use case? Do you already have a data set?
>> 
>>> 
>>> Thanks,
>>> 
>>> Anatoliy
>> 
>> /Manuel
>> 
>> --
>> Manuel Blechschmidt
>> Dortustr. 57
>> 14467 Potsdam
>> Mobil: 0173/6322621
>> Twitter: http://twitter.com/Manuel_B
>> 
>> 

-- 
Manuel Blechschmidt
Dortustr. 57
14467 Potsdam
Mobil: 0173/6322621
Twitter: http://twitter.com/Manuel_B


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