Hi Tim, By not having user or preference information, it's not clear to me-- do you mean you have no demographic information, but you have email or some IP address-- some way to track the user?
It is possible to generate recommendations on purchase history, by looking at the user's transactions and inferring a preference from what they buy the most frequently. I used to work for a company that had transaction history, but it was anonymized-- all the user's activity was tied to an anonymous token. They didn't even have the name or gender. If you know a customer's card #, you could relate the card # as their "user_id" and use the count or monetary value of their transactions for a specific item as a preference for that item. Try something like conditional probability-- the probability that you will buy one thing given that you bought another. By generating a set of pairs (item a being the user has bought, and item b being the one they have not purchased), you can determine the probability that they will by item b, given that they bought item A. Still, if you know nothing about a person at all, and don't even have a way to distinguish them on your website, then recommendation won't really help much because how will you actually give the user recommendations? You could consider using market basket analysis to tell you what other items a person might put in his/her cart. I've done market basket analysis before. It is necessary to do a lot of "pruning" with market basket analysis, because a lot of the frequent pairs are not very useful. But through some careful analysis, you may find interesting combinations of items that will help your business in terms of cross selling/promotion. I am looking at sequential basket analysis right now. If I buy items x1 through x4, what is the probability that a certain item will be the next one? You might be able to use something market basket (fpgrowth) or maybe a markov model to determine the next item in sequence. Good luck with this. If you could share the type of data you do have available, it would be helpful. Rachel ________________________________________ From: Tim Smith [timsmit...@hotmail.com] Sent: Friday, January 10, 2014 5:27 PM To: user@mahout.apache.org Subject: Item recommendation w/o users or preferences Say I have a retail organization that doesn't sell a diverse set of products, eg 2000, but has many small transactions. Also say that I don't have any user or preference information. Is it reasonable to use pattern mining (market baskets) and recommend items based on a set of thresholds for support, confidence, and lift? If not, what are my options? "Email Firewall" made the following annotations. ------------------------------------------------------------------------------ Warning: All e-mail sent to this address will be received by the corporate e-mail system, and is subject to archival and review by someone other than the recipient. This e-mail may contain proprietary information and is intended only for the use of the intended recipient(s). If the reader of this message is not the intended recipient(s), you are notified that you have received this message in error and that any review, dissemination, distribution or copying of this message is strictly prohibited. If you have received this message in error, please notify the sender immediately. ==============================================================================
