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From Marius Rabenarivo <mariusrabenar...@gmail.com>
Subject Re: Use of latent informations associated to items with Mahout's SimilarityAnalysis.cooccurrences
Date Sun, 04 Jun 2017 11:09:32 GMT
IMHO, T represents tag it an Anonymous tag (or property) labeling task
and what you propose is Personalized tag (or property) labeling
as described in https://arxiv.org/pdf/1203.4487.pdf (Section 1.4.5 Emerging
new classification) p. 40

2017-06-04 8:14 GMT+04:00 Marius Rabenarivo <mariusrabenarivo@gmail.com>:

> And what the T in the slides is for?
>
> How can we implement it if it's is not implemented yet?
>
> 2017-06-04 8:11 GMT+04:00 Pat Ferrel <pat@occamsmachete.com>:
>
>> Buy purchasing an item with a tag that you have given it, they are
>> displaying a preference for that tag.
>>
>>
>> On Jun 3, 2017, at 12:36 PM, Marius Rabenarivo <
>> mariusrabenarivo@gmail.com> wrote:
>>
>> So the tag here is assumed to be a tag given by the user to an item?
>>
>> I was thinking that it was some kind of tag we give to the item by some
>> mean (classification, LDA, etc)
>>
>> 2017-06-03 21:14 GMT+04:00 Pat Ferrel <pat@occamsmachete.com>:
>>
>>> A = history of all purchases (in the e-com case)
>>> B = history of all tag preferences
>>>
>>> r = [A’A]h_a + [A’B]h_b
>>>
>>> The part in the slides about content-based recs is not needed here
>>> because you have captured them as user preferences.
>>>
>>>
>>> On Jun 2, 2017, at 7:22 PM, Marius Rabenarivo <
>>> mariusrabenarivo@gmail.com> wrote:
>>>
>>> Please correct side to size in my previous e-mail
>>>
>>> 2017-06-03 6:14 GMT+04:00 Marius Rabenarivo <mariusrabenarivo@gmail.com>
>>> :
>>>
>>>> What will be the size of the matrix if we send an event like tag-pref
>>>> We will get a |U|x|T| matrix I think (where T is the set of all tags).
>>>>
>>>> So [AtA] will be a |T| x |T| matrix and we will do a dot product with
>>>> the user history hT to get recommendation right?
>>>>
>>>> I was assuming that A should be of side |U| x |I| where I is the set of
>>>> all items as it should be added to other terms of the whole enchilada
>>>> formula afterwards.
>>>>
>>>> Thank you for your guidance Pat.
>>>>
>>>> 2017-06-02 21:35 GMT+04:00 Pat Ferrel <pat@occamsmachete.com>:
>>>>
>>>>> Please refer to the documents. The “event” is the name of the type
of
>>>>> event or indicator if preference, it implies the type of
>>>>> the targetEntityId. So a “tag-pref’ event would be accompanied by
>>>>> a targetEntityId = tag-id. This is separate from attaching “tag”
properties
>>>>> to items with the $set event for use with filter and boost rules. One
looks
>>>>> at the data as a possible preference indicator and the other is used
to
>>>>> restrict results. This is why we usually name events so they sound like
a
>>>>> user preference of some type, whereas item property values are simply
item
>>>>> attributes, intrinsic to the items and independent of an individual user.
>>>>>
>>>>> The event can have any name that makes sense to you.
>>>>>
>>>>>
>>>>> On Jun 2, 2017, at 9:19 AM, Marius Rabenarivo <
>>>>> mariusrabenarivo@gmail.com> wrote:
>>>>>
>>>>> so, the event field should be the token and targetEntityId the item
>>>>> ID, right?
>>>>>
>>>>> 2017-06-02 20:07 GMT+04:00 Pat Ferrel <pat@occamsmachete.com>:
>>>>>
>>>>>> Yes, each is analyzed separately as a separate event. If you are
>>>>>> using REST you can send up to 50 events in a single array. Some SDKs
may
>>>>>> support this too.
>>>>>>
>>>>>>
>>>>>> On Jun 2, 2017, at 8:56 AM, Marius Rabenarivo <
>>>>>> mariusrabenarivo@gmail.com> wrote:
>>>>>>
>>>>>> So I have to send an event like category-preference for each tag
>>>>>> associated to an item right?
>>>>>>
>>>>>> entityId: userd-id
>>>>>> event: category-preference
>>>>>> targetEntityId : tag/token
>>>>>>
>>>>>> 2017-06-02 19:47 GMT+04:00 Pat Ferrel <pat@occamsmachete.com>:
>>>>>>
>>>>>>> When a user expresses a preference for a tag, word or term as
in
>>>>>>> search or even in content like descriptions, these can be considered
>>>>>>> secondary events. The most useful are tags and search terms in
our
>>>>>>> experience. Content can be used but each term/token needs to
be sent as a
>>>>>>> separate preference while search phrases can be used though again
turning
>>>>>>> them into tokens may be better.
>>>>>>>
>>>>>>> Please looks through the docs here: http://actionml.com/docs/ur
or
>>>>>>> the siide deck here: https://www.slideshare.n
>>>>>>> et/pferrel/unified-recommender-39986309
>>>>>>>
>>>>>>> The major innovation of CCO, the algorithm behind the UR, is
the use
>>>>>>> of these cross-domain indicators. They are not guaranteed to
predict
>>>>>>> conversions but the CCO algo tests them and weights them low
if they do not
>>>>>>> so we tend to test for strength of prediction of the entire category
of
>>>>>>> indictor and drop them if weak or set a minLLR threshold and
filter weak
>>>>>>> individual indicators out.
>>>>>>>
>>>>>>> Technically these are not called latent, that has another meaning
in
>>>>>>> Machine Learning having to do with Latent Factor Analysis.
>>>>>>>
>>>>>>>
>>>>>>> On Jun 1, 2017, at 11:26 PM, Marius Rabenarivo <
>>>>>>> mariusrabenarivo@gmail.com> wrote:
>>>>>>>
>>>>>>> Hello everyone!
>>>>>>>
>>>>>>> Do you have an idea on how to use latent informations associated
to
>>>>>>> items like tag, word vector embedding in Mahout's
>>>>>>> SimilarityAnalysis.cooccurrences?
>>>>>>>
>>>>>>> Regards,
>>>>>>>
>>>>>>> Marius
>>>>>>>
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>>>>>>
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>

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