Well, anyways: To clarify.... I have a pretty simple implementation im
trying to run:
int ret = recommenderJob.run(new String[] {
"--input",args[0],
"--output",args[1],
"--usersFile","/tmp/users.txt",
"--tempDir", "/tmp",
"--similarityClassname", "SIMILARITY_PEARSON_CORRELATION",
And it gets the error described here.... (numUsers.bin not found).
http://web.archiveorange.com/archive/v/y0uRZUrY8BQGOkwWg34i
If i manually create numUsers.bin , then it returns a new exception:
/tmp/preparePreferenceMatrix/ratingMatrix not Found.
So... Im thinking i must be doing something horribly wrong in my
recommender, but cant figure out exactly what?
On Fri, Mar 28, 2014 at 2:29 PM, Jay Vyas <[email protected]> wrote:
> Thanks sebastian. I guess im looking more for some hints on how to use
> the mahout API for this.
>
> 1) Does mahout support pure distributed collaborative filtering ?
>
> 2) If so , is there any available example of how to use the Mahout API for
> this?
>
>
>
>
>
> On Fri, Mar 28, 2014 at 11:56 AM, Sebastian Schelter <[email protected]>wrote:
>
>> Hi Jay,
>>
>> there's not much documentation unfortunately. We're in the process of
>> creating that however. We removed the pseudo-distributed recommender,
>> mainly because nobody ever used it. There are two research papers that
>> could help you with understanding the other two distributed recommenders:
>>
>> For ALS:
>>
>> Distributed Matrix Factorization with MapReduce using a series of
>> Broadcast-Joins, RecSys'13
>>
>> http://ssc.io/wp-content/uploads/2011/12/sys024-schelter.pdf
>>
>> For item-based:
>>
>> Scalable Similarity-Based Neighborhood Methods with MapReduce, RecSys'12
>>
>> http://ssc.io/wp-content/uploads/2012/06/rec11-schelter.pdf
>>
>>
>>
>> On 03/28/2014 02:04 PM, Jay Vyas wrote:
>>
>>> Hi mahout:
>>>
>>> Looking through the source code there are 3 distributed recommenders...
>>>
>>> the als recommender
>>> the item recommender
>>> the pseudo recommender
>>>
>>> Any docs differentiating these?
>>>
>>>
>>
>
>
> --
> Jay Vyas
> http://jayunit100.blogspot.com
>
--
Jay Vyas
http://jayunit100.blogspot.com
