I'l need to defer to one of the other math whizzes on the potential reasons for recommendations for certain users not appearing. My suspicion is that you would either not have sufficient co-occurrence of specific users/items to support a recommendation or you may need to experiment with a different similarity measure.
Anyone else want to weigh in? Sent from my iPhone On Sep 29, 2013, at 1:14 PM, "Deepak Subhramanian" <[email protected]> wrote: > Sorry . My mistake . I am getting the lower ratings for some of the users > and items. But my issue is not solved . I am not getting ratings for some > of the users and some of the ratings. > > My userFile has 8000 users and my itemsFile has 4000 Items . But I get > recommendations for only 5000 users and 1500 items. And the maximum no of > recommendations given is 258. What can be the reasons that there is no > items recommendations for 3000 users and 2500 items. Is it because there is > no similarities exist between those users and items ? > > > On Sun, Sep 29, 2013 at 4:46 PM, Deepak Subhramanian < > [email protected]> wrote: > >> Thanks Nick. As I mentioned earleir I am getting ratings only for the top >> recommended products instead of ratings for 4000 products I am giving >> numRecommendations parameter to 4000 and maxPrefsPerUser to 4000. Should >> it give 4000 items in the list for each user ? For some reasons the >> output for items which are having lower ratings is not displayed. I see >> the default limit is 10. >> >> I am not sure if I am not getting ratings for 4000 items because I am >> passing the wrong options for the mahout version or is it an issue with >> mahout ver 0.7. I am using 0.7 -mahout-examples-0.7-cdh4.3.1.jar . >> >> I see the parameter name changed in the latest version I checked from git >> - 0.9-SNAPSHOT >> >> maxPrefsPerUserConsidered = jobConf.getInt(MAX_PREFS_PER_USER_CONSIDERED, >> DEFAULT_MAX_PREFS_PER_USER_CONSIDERED); >> >> Will using a latest version help ? >> >> >> >> >> >> On Sun, Sep 29, 2013 at 12:29 PM, Martin, Nick <[email protected]> wrote: >> >>> There should be a score after each recommended item (i.e. 123456:2.6) in >>> your output. Lower scores would be the ones you're interested in. >>> >>> Sent from my iPhone >>> >>> On Sep 28, 2013, at 8:25 AM, "Deepak Subhramanian" < >>> [email protected]> wrote: >>> >>>> Hi >>>> >>>> I am trying to predict the ratings for some items for some users using >>> item >>>> based collaborative filtering. I tried using the mahout >>> recommenditembased >>>> , but it shows only the top 10 items or I can increase it by passing the >>>> --numRecommendations parameter. But it doesnt shows items which has >>> lower >>>> predicted rating . What is the best approach to get ratings for items >>> which >>>> has low predicted rating ? >>>> >>>> >>>> I tried this command. >>>> >>>> mahout recommenditembased --input mahoutrecoinput --usersFile >>>> recouserlist --itemsFile recoitemlist --output >>>> /mahoutrecooutputpearsonnew -s SIMILARITY_PEARSON_CORRELATION >>>> --numRecommendations 4000 --maxPrefsPerUser 4000 >>>> >>>> Also I tried using the estimatePreference method on the recommender. >>>> >>>> Please help . >> >> >> >> -- >> Deepak Subhramanian > > > > -- > Deepak Subhramanian
