Re: Cosine Similarity and LogLikelihood not helpful for implicit feedback!

How are you using LLR to compute user similarity? It is normally used to compute item similarity? Also, what is your scale? how many users? how many items? how many actions per user? On Mon, Sep 29, 2014 at 6:24 PM, Parimi Rohit wrote: > Hi, > > I am exploring a random-walk based algorithm

Re: how to get recommendations by using user-user correlation for the given table in this mail

Yes. But I strongly suggest that you not use Pearson Correlation. Use the LLR similarity to compute indicator actions for each vendor. Then use a user's history of actions to score vendors. This is not only much simpler than what you are asking for, it will be more accurate. You should also me

Re: how to get recommendations by using user-user correlation for the given table in this mail

@Pat and @Ted Thank You so much for the replay. I was looking for the solution as Pat suggested, here I want to suggest the Vendors to the User which he not yet used by User taking the history of that User and compare with other user who have rated the common vendors. If we take the table in that

Cosine Similarity and LogLikelihood not helpful for implicit feedback!

Hi, I am exploring a random-walk based algorithm for recommender systems which works by propagating the item preferences for users on the user-user graph. To do this, I have to compute user-user similarity and form a neighborhood. I have tried the following three simple techniques to compute the s

Re: how to get recommendations by using user-user correlation for the given table in this mail

I would recommend that you look at actions other than ratings as well. Did a user expand and read 1 review? did they read >3 reviews? Did they mark a rating as useful? Did they ask for contact information? You know your system better than I possibly could, but using other information in additi

Re: how to get recommendations by using user-user correlation for the given table in this mail

You have users, services, and vendors. You should decide what you want to recommend. Service? Vendor? Service of Vendor? Assuming the latter combine the services and vendors into a single ID space: vendor1-service1, vendor1-service2 … Then decide what method you want to create recs. We are gene

Re: Streaming K Means

This was replied to earlier with the details u r looking for, repeating here again: See http://stackoverflow.com/questions/17272296/how-to-use-mahout-streaming-k-means/18090471#18090471 for how to invoke Streaming Kmeans Also look at examples/bin/cluster-reuters.sh for the Streaming KMeans optio

how to get recommendations by using user-user correlation for the given table in this mail

Hi all, I have table something looks like in DB : ​​​ rating table ​ Thanks and Regards, Vinayak B

Streaming K Means

Hello everyone, I have previously asked a question about Streaming K Means examples, and got an answer that there are not so many available. Can anyone give me example of how to call Streaming K Means clustering for a dataset, and how to get the results? What are the results, are they the s