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Recommender Systems: We're doing it (all) wrong

technocalifornia.blogspot.com

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Re: Recommender Systems: We're doing it (all) wrong

#31

Post by nkurz »

_delirium wrote: post #10

The prediction context is somewhat different than the analysis context, I think. For predictive recommender systems, the most relevant part of this analysis is the critique of error measures. It may well be that MSE is not an error measure that aligns with the system's actual accuracy goals (e.g. something like perceived quality of the recommendations). When it comes down to it, the end goal is just to predict whethe…

I'd add an alternative:

  #3: Suggest items that they are likely to really love.
This is subtly different than predicting what the user is most likely to like. To optimize with RMSE scoring, you are better off suggesting a sure "4" than a risky "5". For buying an expensive item like a car or a stereo, the safe bet might be a good approach. But for books, music, or movies --- easily sampled, one of a series --- I'd be much more excited by a system that can predict A+ items with even 25% probability than one that offers up straight B items with 80% consistency.

Re: Recommender Systems: We're doing it (all) wrong

#32

Post by farout »

my 2 cents:

When I was doing recommender for a pet supplies company, I used log likelihood test.

Given they product A, what are the chances they would buy B.

Also since we had thousands of products I sometimes looked at correlations charts or even simple histogram to easily pinpoint what products and quantities were purchased after the initial purchase of A. It made crunching millions of transactions easier.

Re: Recommender Systems: We're doing it (all) wrong

#33

Post by frak_your_couch »

xamat wrote: post #28
frak_your_couch wrote: post #19

Earlier quoted context omitted.

I just wanted to point out that the link on your blog to PureSVD points to the wikipedia page for Discounted Cumulative Gain.

OOps! Thanks... just fixed it.

Hey, sorry, one more time. The updated link is also wrong, it's relative to your blog rather than absolute i.e. http://technocalifornia.blogspot.com/2011/04/research.yahoo.... as opposed to http://research.yahoo.com/files/recsys2010_submission_150.pd...

Re: Recommender Systems: We're doing it (all) wrong

#34

Post by xamat »

NY_USA_Hacker wrote: post #30

This article is a great example of why 'computer science' should not assume that they understand statistics or even much in data manipulation. Then the article is an example of why computer people should be careful on where they learn their statistics! The article is awash in hand wringing about "interval scale" and "ordinal scale" data without being at all clear on just why someone should care, and for all the rest…

Thanks @NY_USA_Hacker Yours is a great example of why smart people should also invest in improving communication and social skills. Half of your comment is nonsense. The other half does raise interesting points that would deserve a reply if they were written in a different tone. I would be happy to go into each of the points you mention if you decide to re-write the comment in a more constructive way.

Really, you can be positive, constructive and even happy in your life without sounding less smart by doing so.

Re: Recommender Systems: We're doing it (all) wrong

#35

Post by xamat »

frak_your_couch wrote: post #33
xamat wrote: post #28

Earlier quoted context omitted.

OOps! Thanks... just fixed it.

Hey, sorry, one more time. The updated link is also wrong, it's relative to your blog rather than absolute i.e. http://technocalifornia.blogspot.com/2011/04/research.yahoo.... as opposed to http://research.yahoo.com/files/recsys2010_submission_150.pd...

Oh man... damn blogger. Fixed it now... finally! Thanks!!!

Re: Recommender Systems: We're doing it (all) wrong

#36

Post by NY_USA_Hacker »

xamat wrote: post #34
NY_USA_Hacker wrote: post #30

This article is a great example of why 'computer science' should not assume that they understand statistics or even much in data manipulation. Then the article is an example of why computer people should be careful on where they learn their statistics! The article is awash in hand wringing about "interval scale" and "ordinal scale" data without being at all clear on just why someone should care, and for all the rest…

Thanks @NY_USA_Hacker Yours is a great example of why smart people should also invest in improving communication and social skills. Half of your comment is nonsense . The other half does raise interesting points that would deserve a reply if they were written in a different tone. I would be happy to go into each of the points you mention if you decide to re-write the comment in a more constructive way. Really, you ca…

Your response is to style, not substance.

But there isn't a lot of room to respond with substance because the article is, did I mention, nonsense.

There is a reason: Several paths led to some of the more central topics in probability and statistics. Such paths included gambling, astronomical observations, psychological testing, signal processing, control theory, quality control, 'statistical' physics, quantum mechanics, mathematical models in the social sciences, experimental design, especially in agriculture, mathematical finance, and more. In addition there is now a very solid, polished field of probability, stochastic processes, and their statistics,

Some of these paths got lost in the swamp on their way to some reasonably clear understanding. For the solid material, so far that is rarely taught: The prerequisites need quite a lot of pure math, and then the pure math departments rarely follow through with the probability, stochastic processes, and statistics.

Early in my career, I was dropped into parts of the swamp, but later I got the rest of the pure math prerequisites and good coverage of the solid, polished material.

So, at this point I see both the swamp and the solid, polished material.

Net, the paper is from the swamp, and I responded with just a little of the solid, polished material.

For the swamp, not a lot of discussion is justified. The best response is the one I gave: The stuff from the swamp is nonsense. That may sound harsh, but it's on the center of the target.

Re: Recommender Systems: We're doing it (all) wrong

#37

Post by xamat »

NY_USA_Hacker wrote: post #36
xamat wrote: post #34

Earlier quoted context omitted.

Thanks @NY_USA_Hacker Yours is a great example of why smart people should also invest in improving communication and social skills. Half of your comment is nonsense . The other half does raise interesting points that would deserve a reply if they were written in a different tone. I would be happy to go into each of the points you mention if you decide to re-write the comment in a more constructive way. Really, you ca…

Your response is to style, not substance. But there isn't a lot of room to respond with substance because the article is, did I mention, nonsense. There is a reason: Several paths led to some of the more central topics in probability and statistics. Such paths included gambling, astronomical observations, psychological testing, signal processing, control theory, quality control, 'statistical' physics, quantum mechani…

Good luck with your life out of the swamp. Looks like you are going to need it.

Re: Recommender Systems: We're doing it (all) wrong

#38

Post by xamat »

bigiain wrote: post #4

Meta quibble... Is it just me who starts reading articles like this, only to crash into sentences like this one: "A Likert scale is a unidimensional scale on which the respondent expresses the level of agreement to a statement - typically in a 1 to 5 scale in which 1 is strongly disagree and 5 is strongly disagree." And think snarky comments like "I should keep reading this article. Do I 1) strongly disagree or 5) st…

Thanks for reporting the mistake... In a troll-style, but still helpful. Thanks!
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