Questions tagged [recommender-system]

A recommendation engine tries to predict how much a user will enjoy certain goods (movies, books, songs, etc) and makes recommendations. They are often used by online vendors to suggest new purchases.

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22
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3answers
6k views

What happens when you apply SVD to a collaborative filtering problem? What is the difference between the two?

In Collaborative filtering, we have values that are not filled in. Suppose a user did not watch a movie then we have to put an 'na' in there. If I am going to take an SVD of this matrix, then I have ...
31
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5answers
38k views

How do I use the SVD in collaborative filtering?

I'm a bit confused with how the SVD is used in collaborative filtering. Suppose I have a social graph, and I build an adjacency matrix from the edges, then take an SVD (let's forget about ...
14
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3answers
1k views

Dynamic recommender systems

A Recommender System would measure the correlation between ratings of different users and yield recommendations for a given user about the items which may be of interest to him. However, tastes ...
7
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2answers
1k views

Matrix Factorization algorithms for Recommender Systems

I need to learn about Matrix Factorization for recommender systems, so I downloaded this paper https://datajobs.com/data-science-repo/Recommender-Systems-[Netflix].pdf but I found it too shallow. It ...
5
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1answer
835 views

What is the advantage of non-negativity in matrix factorization?

I am wondering why matrix factorization techniques in the machine learning domain almost always expect the provided matrix to be non-negative. What is the advantage of this constraint? Background: I ...
3
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1answer
296 views

Amount and sparsity of data for recommender systems

I'm starting to work in a project that will have a recommender system as one of its components. I'm trying to figure out if I have the right type of data for the recommender. The data contains ...
3
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2answers
489 views

How to treat rare / new items in the validation of a recommender system?

I'm working on movie recommendation algorithm. The data set consists of about 40 million ratings (user, film, rating). I want to separate the ratings into two groups - training set and probe set. The ...
13
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7answers
4k views

Recommendation for a book about recommender systems

Can you recommend a book with good information that can be applied to developing a recommender system?
13
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2answers
472 views

Converting a list of partial rankings into a global ranking

I'm working on something like the following problem. I have a bunch of users and N books. Each user creates an ordered ranking of all the books he's read (which is likely a subset of the N books), e.g....
12
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3answers
6k views

SVD of a matrix with missing values

Suppose I have a Netflix-style recommendation matrix, and I want to build a model that predicts potential future movie ratings for a given user. Using Simon Funk's approach, one would use stochastic ...
8
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2answers
4k views

Does it make sense to measure recall in recommender systems?

Assume I've built a recommender system that (given say movie rankings or whatever of many users) will produce a list of 10 recommended movies for each user to watch. Imagine that I also have some ...
3
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2answers
723 views

How to integrate users' profile information into a recommender system

I need to build a recommendation system with lots of information about users (age, sex, location, income etc), but very sparse information about users' prefernces (i.e 1-2 products consumed out of 100 ...
6
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1answer
396 views

Conditional Logit for recommender systems?

Are conditional multinomial logits used for recommendation engines? Although they are commonly used in econometrics, I've never heard it used or discussed in the context of recommender systems. ...
4
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1answer
3k views

Evaluating matrix factorization algorithms for Netflix

I've been trying to implement Simon Funk's movie recommendation algorithm explained here. I understand how the user and item factors are computed. However the evaluation method is not clearly ...
7
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1answer
4k views

Evaluating recommender systems with (implicit) binary ratings only

I'm analyzing a set of news articles and user libraries. User library is the set of news articles shared by one user. Obviously, the rating is 1 (the article is in user's library) and 0, otherwise. I ...
2
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2answers
1k views

Algorithm to calculate difference in users' tastes

I have data like Person $A$ like movies ['X','Y', 'Z'] and he dislikes ['V']. Person $B$ like movies ...
4
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1answer
243 views

How to Deal with Categorical Variables that Allow Selection of Multiple Values per Observation?

Say you are dealing with a movie database that has movies and their genres. Genre is a categorical variable but each movie can belong to more than one genre. For example, Movie A may be Comedy and ...
4
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4answers
635 views

What are good introductory papers on recommender systems?

I am beginning to build a recommendation system. I have users on a website and they purchase services, so I'll recommend services that commonly go along - i.e. are purchased by a single user (not ...
4
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2answers
1k views

Matrix Factorization Recommendation Systems with Only “Like” Ratings

I'm trying to build a recommendation system, but I only have data on what my users have "liked", i.e. all non-missing data has the same numeric value. Is it possible for me to use matrix ...
3
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1answer
668 views

Updating SVD in Recommender Systems for change in ratings

I have read that there are projection based methods to accomodate for new user's ratings or for the ratings for a new item in SVD. However, I want to know how to update my feature space for change in ...
3
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1answer
119 views

How to deal with information of variable length?

This is the question arised from my previous question. Basically, I am trying to build a prediction model for movie's rating. So I have to deal with numeric attribute such as ...
0
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0answers
19 views

What is the standard metric used in recommendation systems to evaluate the rankings?

I was searching for a metric to do this for a while and still could not find. More specifically, my problem is as follows. I have a ranked golden corpus. For example, consider that it looks as ...
5
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3answers
399 views

Simple recommender system - where to start?

Without going into specifics, I'm currently working on a system that involves 20-25 questions being answered as either Green, Yellow, Orange or Red. After completing a subset of these questions (many ...
2
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4answers
157 views

Algorithm for rating books: Relative perception

So I am developing this application for rating books (think like IMDB for books) using relational database. Problem statement : Let's say book "A" deserves 8.5 in absolute sense. In case if A is ...
1
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1answer
82 views

How to convert classification features into a ranking function?

I am using 3 features (x1, x2, x3) for binary classification. All my feature values are in 0 to 1 range (unit range). I obtained how important each feature was in classification as follows (i.e. <...
1
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1answer
134 views

Statistical significance of item-to-item relationship

Context: I have an e-commerce application - so I have users and products. I'm trying to build an item-to-item recommendation system based upon user behavior. In particular I'm taking all the users' ...
1
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1answer
721 views

MAE has gotten worse but RMSE is better, how should I interpret it?

I am doing some testing in recommender systems with extended epinions dataset, I implemented two models, model A give me RMSE of 0.5387 and MAE of 0.3111 and model B gave me RMSE of 0.5121 and MAE of ...
1
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2answers
205 views

Most efficient way to set up a questionnaire to get to know a user's taste

I have a solid user-item matrix, with which I have build a collaborative filtering recommender system. I also have for each item a number of high quality features. If a new user comes to the website (...
0
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1answer
936 views

Neural Networks for Content Based Recommendation system

I'm working on the TED Dataset which has the transcript of each TED Talk. I have around 1000 such TED talk transcripts and I need to recommend 3 TED Talks based on the Transcript of these talks. As ...
0
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1answer
113 views

What is a good way to convert movie ratings data (rated from 1 to 5, 5 being the best) to pairwise preferences?

I am working with movielens 100k, which is a dataset with 100,000 ratings of movies, rated by 943 users on 1640 movies. I need to convert these ratings to pairwise preferences between movies for every ...