predictionio-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Cody Kimball <cody-kimb...@pluralsight.com>
Subject Re: PredictionIO return array of objects
Date Sat, 17 Jun 2017 04:13:44 GMT
It is very likely that the metadata will change periodically, so
unfortunately I won't be able to denormalize. A key value store is
certainly a possibility that could be integrated into returned predicted
responses.

@Pat, I went ahead and created that issue with the feature request.
Meantime in effort to maximize the potential and use of PredictionIO I am
trying to see where the properties are being stripped out. I am assuming
this is done in Serving.scala?


On Fri, Jun 16, 2017 at 2:18 PM Donald Szeto <donald@apache.org> wrote:

> It also depends on how much you are willing to denormalize. If your items'
> metadata don't change, it would be fine to send items' metadata in as part
> of the event.
>
> If you cannot denormalize and your scale is huge, you might want to
> consider putting metadata in a KV store.
>
> On Fri, Jun 16, 2017 at 12:19 PM, Pat Ferrel <pat@occamsmachete.com>
> wrote:
>
>> If you are setting properties of items, these are internally returned
>> with the item ids and stripped off from the results before the query
>> response. I think it would be a simple mod to leave them instead of
>> stripping so you’d have to mod the code and later merge with newer updates
>> if they are required.
>>
>> This would require you send $set events to the EventServer with
>> properties for every item but not all possible types are supported and the
>> format of the returned properties is fixed so you would need to deal with
>> that. Basically all attributes must be encoded in named JSON arrays of
>> strings like “image”: [“http://image/url”] etc.
>>
>> This is not the first time we’ve been asked for this so you can add a
>> feature request: https://github.com/actionml/universal-recommender/issues
>>
>>
>> On Jun 16, 2017, at 10:55 AM, Cody Kimball <cody-kimball@pluralsight.com>
>> wrote:
>>
>> Sorry yes, I am using the Universal Recommender put up by ActionML.
>>
>> I am hoping to avoid spinning up another service to simply return the
>> queried results (title, description, image) to augment the prediction
>> results. However, if that is the only way to do this, then I'll follow down
>> that path.
>>
>> On Fri, Jun 16, 2017 at 11:27 AM Pat Ferrel <pat@occamsmachete.com>
>> wrote:
>>
>>> What template? Generally this requires you take the id and make a query
>>> to your catalog DB.
>>>
>>>
>>> On Jun 16, 2017, at 9:50 AM, Cody Kimball <cody-kimball@pluralsight.com>
>>> wrote:
>>>
>>> Architectural Design Question:
>>>
>>> I have a model that performs as expected and returns an array of ID's
>>> with their associated scores. Now as I am trying to get the PIO response to
>>> render their associated pieces of content on our website, it looks like I
>>> will need not only those IDs but other meta tag values as well to render
>>> the pieces of content on the website properly.
>>>
>>> My question is can the PredictionIO response array of objects be easily
>>> configured to return the TargetEntityID and score, as exists currently, as
>>> well as with a few specific items it pulls from the property list?
>>>
>>> example:
>>>
>>> {
>>>   "itemScores":[
>>>     {"item":"22","score":4.072304374729956, "title":"title1",
>>> "description":"helpful meta description1", "image":"imageurl1"},
>>>     {"item":"62","score":4.058482414005789, "title":"title2",
>>> "description":"helpful meta description2", "image":"imageurl2"},
>>>     {"item":"75","score":4.046063009943821, "title":"title3",
>>> "description":"helpful meta description3", "image":"imageurl3"},
>>>     {"item":"68","score":3.8153661512945325, "title":"title4",
>>> "description":"helpful meta description4", "image":"imageurl4"}
>>>   ]
>>> }
>>>
>>> Or would it make more sense to have the input value for TargetEntityID
>>> be a json object for PredictionIO to train on, possibly by altering the
>>> training model to only use the "ID" attribute from that object to train on?
>>>
>>> itemScores":[
>>>     {"item": {"ID": "22", "title":"title1", "description":"helpful meta
>>> description1", "image":"imageurl1},"score":4.072304374729956},
>>>
>>> Or even I could fudge the model to have targetEntityID be a large
>>> concatenated value, which in my mind seems like problems waiting to happen.
>>>
>>> itemScores":[
>>>     {"item": "22 || title1 || helpful meta description1 || imageurl1"}
>>> ,"score":4.072304374729956},
>>>
>>> --
>>> *Cody Kimball*
>>> Revenue Engineer
>>>
>>>  Don't Just Keep Up With Technology. Master It!
>>> <https://www.pluralsight.com/>
>>>
>>>
>>> --
>> *Cody Kimball*
>> Revenue Engineer
>>
>>  Don't Just Keep Up With Technology. Master It!
>> <https://www.pluralsight.com/>
>>
>>
>>
> --
*Cody Kimball*
Revenue Engineer

 Don't Just Keep Up With Technology. Master It!
<https://www.pluralsight.com/>

Mime
View raw message