# Collaborative Filtering

**URL:** <https://discuss.elastic.co/t/collaborative-filtering/126143>\
**Category:** Elasticsearch\
**Created:** [March 29, 2018, 6:27pm UTC](https://discuss.elastic.co/t/collaborative-filtering/126143 "2018-03-29T18:27:23Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![jonas-schulze](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/jonas-schulze/32/29377_2.png) [@jonas-schulze](https://discuss.elastic.co/u/jonas-schulze)\
**Post date:** [March 29, 2018, 6:27pm UTC](https://discuss.elastic.co/t/collaborative-filtering/126143/1 "2018-03-29T18:27:24Z")

</div>

Hi everybody,

disclaimer: I am not experienced at all with Elasticsearch.

I'd like to implement some collaborative filtering following a short example from [Trey Grainger](https://www.slideshare.net/treygrainger/building-a-real-time-solrpowered-recommendation-engine), slides 28ff, where he wants to recommend books to potential buyers.  
In the given example, suppose we are looking for recommendations for `user5` and we have stored the data like this:

```auto
{
  "mappings": {
    "purchase": {
      "properties": {
        "book_id": { "type": "integer" },
        "user_id": { "type": "integer" }
      }
    }
  }
}

```

In order to reduce the amount of data transferred from the ES cluster, eventually, I'd like to do all of this in a single query.  
Also, I'm not bound to this representation of the data. If a different representation would make this significantly easier, I'd be happy to know.

For now, I tried this using multiple queries. First, I get the books that user 5 likes (books 1 and 4), and afterwards similar users (users 1 and 4, having 1 and 2 shared purchases, respectively). Hence, I'd like to boost the book recommendations based on user 4 by a factor of 2 (size of overlap in purchases with user 5). My current (not-working) draft looks like this:

```auto
curl -sXPOST 'http://localhost:9200/purchases/purchase/_search' -d '{
  "query": {
    "terms": {
      "user_id": [1,4]
    }
  },
  "size": 0,
  "aggs": {
    "recommendations": {
      "terms": {
        "field": "book_id",
        "exclude": [1,4]
      },
      "aggs": {
        "score": {
          "sum": {
            "script": {
              "inline": """
                if (doc['user_id'] == 4) {
                  return 2
                }
                if (doc['user_id'] == 1) {
                  return 1
                }
              """
            }
          }
        }
      }
    }
  }
}

```

What am I doing wrong?  
Am I on the right track?  
Is this a easier to solve using Elasticsearch Graph (X-Pack), and if so: how?  
How would I eventually do all of this using a single query (that I only provide with the user I want to get the recommendations for)?

Any help is greatly appreciated! Also, my companies ES cluster is running version 2.3.0 ... we have plans to upgrade to a recent 5.x, but this is not feasible in the short term.

Best, Jonas

---

<div class="post-metadata">

**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\
**Post date:** [April 26, 2018, 6:27pm UTC](https://discuss.elastic.co/t/collaborative-filtering/126143/2 "2018-04-26T18:27:30Z")

</div>

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