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Questions tagged [recommendation-engine]

For questions relating to recommendation engines, collaborative filtering, and personalization. Questions tend to be algorithmic or statistical in nature.

Recommendation engines are systems that suggest (recommend) to users various items for consideration. Some of the best known real world usage occurs at many major internet sites, such as Netflix, Amazon, Google, Yahoo, Pandora, last.fm, and others.

The input of such algorithms are most commonly the past purchases of the user, the rating the user gave to other goods, the items that have been purchased together ("customer who bought this also bought..."), the browsing history, etc.

For this tag, it is recommended that users focus on mathematical or statistical clarity, as it is a particularly advanced topic and implementation can take quite a bit of computational effort.

See also wikipedia.

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Recommender: Log user actions & datamine it – good solution

I am planning to log all user actions like viewed page, tag etc. What would be a good lean solution to data-mine this data to get recommendations? Say like: Figure all the interests from the viewed URL (assuming I know the associated tags)…
Quintin Par
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Architecture & Essential Components of StumbleUpon's Recommendation Engine

I would like to know how stumbleupon recommends articles for its users?. Is it using a neural network or some sort of machine-learning algorithms or is it actually recommending articles based on what the user 'liked' or is it simply recommending…
jvc
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Appending pandas DataFrame with MultiIndex with data containing new labels, but preserving the integer positions of the old MultiIndex

Base scenario For a recommendation service I am training a matrix factorization model (LightFM) on a set of user-item interactions. For the matrix factorization model to yield the best results, I need to map my user and item IDs to a continuous…
Fulco
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Spark MLlib - Collaborative Filtering Implicit Feed

So I am building an implicit feedback recommender model with Spark 1.0.0 and I am trying to follow the example they have on their collaborative filtering…
atellez
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Apache Mahout Performance Issues

I have been working with Mahout in the past few days trying to create a recommendation engine. The project I'm working on has the following data: 12M users 2M items 18M user-item boolean recommendations I am now experimenting with 1/3 of the full…
Daniel Zohar
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Developing a web application in python with neo4j

I'm planning to implement a recommendation engine, of which details are given here. 'Python' is my preferred choice along with 'neo4j' Database. Can anyone please point out, how integration of 'neo4j' with any web framework like 'django' can be…
jvc
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How to Implement A Recommendation System?

I've Collective Intelligence book, but I'm not sure how it can be apply in practical. Let say I have a PHP website with mySQL database. User can insert articles with title and content in the database. For the sake of simplicity, we just compare the…
Azam
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Methods for Lazy Initialization with properties

I'm currently altering a widely used class to move as much of the expensive initialization from the class constructor into Lazy Initialized properties. Below is an example (in c#): Before: public class ClassA { public readonly ClassB B; …
Stu Pegg
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How training LSTM model for sequences items ?

I try to use the LSTM model for the next basket recommendation. I would like to apply the same approach that this article : A Dynamic Recurrent Model for Next Basket Recommendation In my case, I have some users, which are buying some items at…
beubeu
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How to create a multi-column recommendation engine in postgresql?

I have a table in postgresql containing some cars +1000000 records: +----+--------+------+---------+-----------+-------------+------------+------------+ | id | price | year | mileage | fuel_type | body_type | brand | model …
Niels Kristian
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How to deal with missing values in python scikit NMF

I am trying to apply NMF on my dataset, using python scikit-learn. My dataset contains 0 values and missing values. But scikit-learn does not allow NaN value in data matrix. Some posts said that replace missing values with zeros. my questions…
Zhaojie Tao
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How to build a sparse matrix in PySpark?

I am new to Spark. I would like to make a sparse matrix a user-id item-id matrix specifically for a recommendation engine. I know how I would do this in python. How does one do this in PySpark? Here is how I would have done it in matrix. The table…
ashish trehan
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How can I handle new users/items in model generated by Spark ALS from MLlib?

currently when a new user comes I cannot update my recommender system which apprently is related to not having added the user and item matrix. Where can I find this and how to do this? Thanks model.userFactors model.itemFactors
peter
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Automatic music rating based on listening habits

I've created a Winamp-like music player in Delphi. Not so complex, of course. Just a simple one. But now I would like to add a more complex feature: Songs in the library should be automatically rated based on the user's listening habits. This means:…
caw
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How to do an item based recommendation in spark mllib?

In Mahout, there is support for item based recommendation using API method: ItemBasedRecommender.mostSimilarItems(int productid, int maxResults, Rescorer rescorer) But in Spark Mllib, it appears that the APIs within ALS can fetch recommended…
user321532
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