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From "Martin, Nick" <>
Subject RE: get similar items
Date Wed, 12 Feb 2014 15:04:23 GMT
Yeah, since it would appear you're lacking requisite data for recommenders the only other thing
I can think of in this case is potentially treating the movie records as documents and clustering
them (via whatever might be in the 'description' field).

Have a look here
and see if you can support something like this with your dataset.

-----Original Message-----
From: Sebastian Schelter [] 
Sent: Wednesday, February 12, 2014 6:28 AM
Subject: Re: get similar items


Mahout's recommenders are based on analyzing interactions between users and items/movies,
e.g. ratings or counts how often the movie was watched.

On 02/12/2014 11:34 AM, N! wrote:
> Hi all:
>   Does anyone have any suggestions for the questions below?
>   thanks a lot.
> ------------------ Original ------------------
> Sender: "N!"<>;
> Send time: Wednesday, Feb 12, 2014 6:17 PM
> To: "user"<>;
> Subject: Re: get similar items
> Hi Sean:
>              Thanks for the reply.
>              Assume I have only one table named 'movie' with 1000+ records, this table
have three columns:'id','movieName','movieDescription'.
>              Can Mahout calculate the most similar movies for a movie.(based on only
the 'movie' table)?
>              code like: List mostSimilarMovieList = recommender.mostSimilar(int movieId).
>              if not, do you have any suggestions for this scenario?

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