# Tagged Questions

69 views

### Incremental SVD in Collaborative Filtering

In the so-called incremental SVD used for collaborative filtering: http://www.machinelearning.org/proceedings/icml2007/papers/407.pdf http://www2.research.att.com/~volinsky/papers/ieeecomputer.pdf ...
80 views

### How to compute K and n? [Item-based Collaborative Filtering]

I'm currently studying an item-based collaborative filtering algorithm described in Ul Haq, Raza - Hybrid Recommender System Towards User Satisfaction. I've formulated the algorithm below based on it. ...
384 views

### Best machine learning approach for recommendation engine?

I am given a dataset where there are people profiles and the types of beer each person likes, given in a list. What is the best way to find relevant beers given a specific beer based on this data? ...
121 views

### Design data sets for a movie recommendation algorithm

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 ...
131 views

### Adding content information to matrix factorization-based recommender

I'm currently using a matrix factorization method to generate recommendations (for info on this, check: Matrix Factorization Techniques for Recommender Systems). At the moment, my rating estimate is ...
206 views

### Matrix factorization and gradient descent for recommender systems; user bias?

I've been reading about using Matrix Factorization techniques to do collaborative filtering. A popular thing to do seems to be to add user and item biases into the ratings prediction. What I don't ...
114 views

### Most relevant algorithms for Collaborative Filtering to test against

I am working on algorithms for collaborative filtering (CF). As part of this work, I want to compare a new algorithm to previous approaches to the problem. I am also surveying the most important ...
79 views

### Appropriate threshold to map a similarity value to an edge in a graph

In order to cluster users given a user-item binary matrix data, I am planning to first find user's similarity (Jaccard) and then use graph theory to isolate clusters (communities). I need to map the ...
105 views

### Matrix factorization vs random walk with restart for recommender systems

Suppose I want to handle "friend recommendation" problem on a large social network graph. I came across random-walk-with-restart as one technique used. I was thinking of using matrix factorization as ...
84 views

### Hierarchical recommender

I have a hierarchical feature matrix, By that I mean that each item may belongs to one or more category, so my data will look something like that |  User |  Categ  | Item  | ...
87 views

### Collaborative filtering through matrix factorization with logistic loss function

Consider collaborative filtering problem. We have matrix $M$ of size #users * #items. $M_{i,j} = 1$ if user i likes item j, $M_{i,j} = 0$ if user i dislikes item j and $M_{i,j}=?$ if there is no data ...
645 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 ...
76 views

### Clustering groups based on frequency and last date of choice

I have data coming in the following format: UserId, GroupId, Frequency (how many times the user chose the group), Max timestamp (the last time the user chose the group). Based on this dataset we need ...
264 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 ...
89 views

### What is a distance or similarity metric that takes into account the improbability of a match?

Suppose I want to measure similarity between users. If two users match on an item that is very improbable, I want to give greater weight to that.
81 views

### Dynamic recommender systems [duplicate]

Possible Duplicate: Dynamic recommender systems A Recommender System would measure the correlation between ratings of different users and yield recommendations for a given user about the ...
535 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?