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Improving Recommendation Systems

To predict customers’ preferences, compare similar products

MIT News
Wed, 07/13/2011 - 11:45
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Recommendation algorithms are a vital part of doing business on the Internet. They provide the basis of the targeted advertisements that account for most commercial sites’ revenues, and of services such as Pandora, the radio site that tailors song selections to listeners’ declared preferences. The DVD rental site Netflix deemed its recommendation algorithms important enough that it offered a million-dollar prize to anyone who could improve the site’s predictions by 10 percent.

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But Devavrat Shah, the Jamieson Career Development Associate Professor of Electrical Engineering and Computer Science in MIT’s Laboratory of Information and Decisions Systems, thinks that the most common approach to recommendation systems is fundamentally flawed. Shah believes that, instead of asking users to rate products on, say, a five-star scale, as Netflix and Amazon do, recommendation systems should ask users to compare products in pairs.

 …

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Submitted by Jitendranath.p on Tue, 03/20/2012 - 09:27

Good attempt,Author mentioned

Good attempt,Author mentioned that Comparision is better than ranking,however there should be strong parameters defined for comparision,without which it will be a futile attempt. in my opinion, its not worth to depend on ranking system(Though ranking system is a broad concept ranging from Individual ranking system to Organization ranking system- For individual ranking system 0 read "punished by rewards book" and for Organization ranking system- read performance measurement -transformation-by David sptizer).coming to "comparision" method, it just helps you to understand your current state compare to other similar lines.however comparision can not be made accurate as its not at all possible to consider all the factors involved statistically.Hence, The concept of improving recommendation system is not useful. The best metric to know the customer preference is to conduct trend analysis or refer your sales data over a period of time. unless and untill your inventory gets converted into dollors you can not actually realize wat are the customer preferene.after all,its a business..so bottomline should deal with economics.Refer the good article herehttp://www.qualitydigest.com/sept00/html/satisfaction.html,http://jitendranath.palem.in/blog/http://jitendranath.palem.in/blog/

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