Hi, I just begin to learn Mahout and have not got the chance to read the code. But according to the book "Mahout in Action", first paragraph on page 59, also the psedo-code on page 57 for the algorithm, the user already has a list of itmes of which he has preference, thus implicitly define the "neighbor" for the target item. (Another way to state it is, for user-based recommendation, since usually the number of user is very large, we need to have a limited number of similar user to model the target user. However, for item based recommendation, for a perticular user, the items he shows references is already limited, thus we will use all of them as the neighbor for the target item.)
Just my 2 cents -zhipeng --- On Mon, 11/26/12, Evgeny Karataev <[email protected]> wrote: > From: Evgeny Karataev <[email protected]> > Subject: Item-based no neighbourhood > To: "user" <[email protected]> > Date: Monday, November 26, 2012, 9:59 PM > Hello, > > Are there any particular reasons, why the implementation of > item-based > recommendations does not support item neighborhood > formation, e.g. based on > similarity threshold or by providing a number for the most > similar items to > be used? > > I know that there is linear interpolation item-based > recommendation, but it > seems a little bit different than just classical item-based > recommendation. > And anyway it does not support threshold based > neighborhood. > > Thank you. > > -- > Best Regards, > Evgeny Karataev >
