Hi Marco, thank you for pointing me to this direction.
Again I have to ask: What would be more efficient? Rescoring or CandidateItemStrategy? Where are the differences? Thanks! Am 04.07.2011 12:39, schrieb Marko Ciric: > > Hi Em, > > If I understood well what you're asking, you could implement a new > CandidateItemStrategy class. If you see that interface, there's this > method getCandidateItems(long userID, DataModel dataModel) that has all > parameters you need in order to filter out items that belong to the > unwanted category. > This class is actually used inside an item-based recommender. > > On 07/02/2011 03:53 PM, Em wrote: >> Hi Steven, >> >> That would be the alternative. Create different data-models per >> category, yes. >> >> Does this affect the quality of your recommendations in comparison to a >> data-model that contains also not-relevant data for the current >> category/situation/social-graph but the unwanted recommendations are >> filtered out by a Rescorer? >> >> Regards, >> Em >> >> Am 02.07.2011 15:22, schrieb Steven Bourke: >>> Assuming you have the technical resources, one approach could involve >>> just >>> containing different 'conditions' into different data models. >>> >>> For instance I have one setup that only has users from someones social >>> graph, and another that includes all my users. When generating >>> recommendations I just point it to whichever datasource is required. >>> >>> >>> On Fri, Jul 1, 2011 at 7:25 PM, Sean Owen<sro...@gmail.com> wrote: >>> >>>> From what you describe so far, you do not need any new code. A >>>> Rescorer does what you want, I believe. If not, maybe you can explain >>>> more about what it's not doing that you want it to do. A Rescorer to >>>> exclude items is probably always a good idea as it saves computation. >>>> >>>> On Fri, Jul 1, 2011 at 7:03 PM, Em<mailformailingli...@yahoo.de> >>>> wrote: >>>>> Hi Sean, >>>>> >>>>> I am not very familiar with the code itself, however I have no problem >>>>> with digging into it. >>>>> >>>>> I guess the CandidateItemStrategy and the Rescorer are usable for all >>>>> kinds of recommendations: user-user, user-item, item-item etc. and >>>>> so I >>>>> can create a generic (or general) implementation for the problem? >>>>> >>>>> Could you explain more of the tradeoffs for both >>>>> implementation-possibilities, please? >>>>> >>>>> Regards, >>>>> Em >>>>> >>>>> Am 01.07.2011 19:01, schrieb Sean Owen: >>>>>> The short answer is that you'd have to modify the code to inject this >>>>>> kind of logic -- though you might get away with just using a custom >>>>>> CandidateItemStrategy in an item-based recommender. >>>>>> >>>>>> A Rescorer will cause it to not bother computing estimated values for >>>>>> unwanted items though, so I think it already does what you intend. >>>>>> >>>>>> On Fri, Jul 1, 2011 at 5:56 PM, Em<mailformailingli...@yahoo.de> >>>> wrote: >>>>>>> Hello list, >>>>>>> >>>>>>> is it possible to filter out some items/users from the >>>>>>> recommendation-process? >>>>>>> >>>>>>> In some cases one does not want to include information from some >>>> sources in >>>>>>> special situations. >>>>>>> >>>>>>> As an example you can imagine an onlineshop. If you click on the >>>> category >>>>>>> "women" it would be the best to only show recommendations for this >>>>>>> main-category rather than also showing some stuff for men. >>>>>>> >>>>>>> A Rescorer could be a solution to filter out those unwanted results >>>> *after* >>>>>>> the big part is done (am I correct?), however I do not want to spend >>>>>>> ressources on computing probabilities for items that are definitly >>>> unwanted >>>>>>> for the resultset. >>>>>>> >>>>>>> What I want is something like a >>>>>>> SELECT col1, col2, col3 FROM myData WHERE category = "women" OR >>>> category = >>>>>>> "subcategoryOfWomen" >>>>>>> and than do the computation on top of this dataset. >>>>>>> >>>>>>> Is this possible with Mahout? >>>>>>> >>>>>>> Regards, >>>>>>> Em >>>>>>> >>>>>>> -- >>>>>>> View this message in context: >>>> http://lucene.472066.n3.nabble.com/Exclude-by-RuleSet-tp3129982p3129982.html >>>> >>>>>>> Sent from the Mahout User List mailing list archive at Nabble.com. >>>>>>> > >
