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Search criteria: RecommenderJob.
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Re: Problems with Mahout's RecommenderIRStatsEvaluator - Mahout - [mail # user]
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...Sean I think it is still a supervised learning problem in that there is a labelled training data set and an unlabeled test data set. Learning a ranking doesn't change the basic ...
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Author: Ted Dunning,
2013-02-16, 23:15
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Re: Problems with Mahout's RecommenderIRStatsEvaluator - Mahout - [mail # user]
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...There are a variety of common time based effects which make time splits best in many practical cases. Having the training data all be from the past emulates this better than random spl...
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Author: Ted Dunning,
2013-02-16, 23:12
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Re: (near) real time recommender/predictor - Mahout - [mail # user]
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...On Sat, Feb 2, 2013 at 1:03 PM, Pat Ferrel wrote: No. I agree with it. Human relatedness decays much more quickly than item popularity. I was extending this. &...
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Author: Ted Dunning,
2013-02-02, 21:25
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Re: (near) real time recommender/predictor - Mahout - [mail # user]
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...Pat, This is an important effect and it strongly informs how you should down-sample heavy users as well as how you should handle temporal dynamics. On Sat, Feb 2, 2013 at 9:54 AM...
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Author: Ted Dunning,
2013-02-02, 19:44
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Re: Available Recommenders' Implementations - Mahout - [mail # user]
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...There is also the stochastic projection code. Search for ssvd in the mailing list archives. Sent from my iPhone On Apr 4, 2012, at 8:36 AM, Sebastian Schelter wrote:...
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Author: Ted Dunning,
2012-04-04, 16:30
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Re: Significant - serendipity in recommending - Mahout - [mail # user]
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... which isn't very interesting. Penaltys for common items is inherent in the LLR score which is commonly used in Mahout recommenders. On Sun, Mar 25, 2012 at 5:52 AM, Steven Bourke wrote: ...
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Author: Ted Dunning,
2012-03-25, 17:57
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Re: Significant - serendipity in recommending - Mahout - [mail # user]
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...I don't know what you mean by significant any more than Sean. But serendipity in a recommender comes from two sources. Both must be present. One source is having enough people who...
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... interact with the recommender. The second source is a judicious injection of exploration which can come from dithering of result lists or from additional exploration opportunities such as a top40...
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Author: Ted Dunning,
2012-03-24, 17:00
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Re: Significant - serendipity in recommending - Mahout - [mail # user]
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...Yeah... you don't usually need a specific mechanism for that. Just get a bunch of people together and they will surprise each other for you. On Sat, Mar 24, 2012 at 2:27 PM, Lee ...
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Author: Ted Dunning,
2012-03-25, 02:34
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Re: Malicious users on recommender system - Mahout - [mail # user]
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.... With the recommendation analysis itself, the key is to flatten all frequency metrics per user. With unsophisticated click fraud, the abuse will center on creating high play frequencies for a few users which...
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... will then be counted as a very small input signal since so few users are doing it and their high play rates won't matter. Also, the major effect if any will be to simply give the fraudsters recommendations...
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Author: Ted Dunning,
2012-08-29, 01:23
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Re: Malicious users on recommender system - Mahout - [mail # user]
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...First off, it looks like Amazon is not filtering for engagement here. Second, you have to have Amazon's prominence before attacks by large groups of people are worth it. Third, t...
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Author: Ted Dunning,
2012-08-29, 06:16
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