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Questions tagged [recommender-system]

Everything related to recommender systems

Everything related to recommender systems

Types of Recommender Systems Some types of recommender systems:

  1. Collaborative Filtering

    • Based on user-interaction data such as "user A watches movie Z"
    • Common methods: Matrix Factorization, Neighborhood Models

  2. Content Based Recommender Systems

    • Based on user and item content such as user demographics, movie genres, actors in the movie, etc
    • Common methods: Classification, Regression
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Meaning of latent features?

I am learning about matrix factorization for recommender systems and I am seeing the term latent features occurring too frequently but I am unable to understand what it means. I know what a feature is but I don't understand the idea of latent…
Jack Twain
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Does click frequency account for relevance?

While building a rank, say for a search engine, or a recommendation system, is it valid to rely on click frequency to determine the relevance of an entry?
Rubens
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Recommending movies with additional features using collaborative filtering

I am trying to build a recommendation system using collaborative filtering. I have the usual [user, movie, rating] information. I would like to incorporate an additional feature like 'language' or 'duration of movie'. I am not sure what techniques I…
Sidhha
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Item based and user based recommendation difference in Mahout

I would like to know how exactly mahout user based and item based recommendation differ from each other. It defines that User-based: Recommend items by finding similar users. This is often harder to scale because of the dynamic nature of…
Sreejithc321
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Preference Matching Algorithm

There's this side project I'm working on where I need to structure a solution to the following problem. I have two groups of people (clients). Group A intends to buy and group B intends to sell a determined product X. The product has a series of…
R.D
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Can I use cosine similarity as a distance metric in a KNN algorithm

Most discussions of KNN mention Euclidean,Manhattan and Hamming distances, but they dont mention cosine similarity metric. Is there a reason for this?
Victor
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Spark ALS: recommending for new users

The question How do I predict the rating for a new user in an ALS model trained in Spark? (New = not seen during training time) The problem I'm following the official Spark ALS tutorial…
ciri
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Which supervised learning algorithms are available for matching?

I'm working on a non-profit where we try to help potential university applicants by matching them with alumni that want to share their experience/wisdom and, at the moment, it is happening manually. So I'll have two tables, one with students and one…
k1nd3rm4x1
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How to split train/test in recommender systems

I am working with the MovieLens10M dataset, predicting user ratings. If I want to fairly evaluate my algorithm, how should I split my training v. test data? By default, I believe the data is split into train v. test sets where 'test' contains…
jamesmf
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Field Aware Factorization Machines

Can anyone explain how field-aware factorization machines (FFM) compare to standard Factorization Machines (FM)? Standard: http://www.ismll.uni-hildesheim.de/pub/pdfs/Rendle2010FM.pdf "Field…
B_Miner
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Create most "average" cosine similarity observation

For a recommendation system I'm using cosine similarity to compute similarities between items. However, for items with small amounts of data I'd like to bin them under a general "average" category (in the general not mathematical sense). To…
eric chiang
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How should one deal with implicit data in recommendation

A recommendation system keeps a log of what recommendations have been made to a particular user and whether that user accepts the recommendation. It's like user_id item_id result 1 4 1 1 7 -1 5 19 1 5 80 …
wdg
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Benchmark datasets for collaborative filtering

I'd like to test a new algorithm for collaborative filtering. A typical use case is to recommend movies based on the preferences of users similar to the specific user. What are some common benchmark datasets that researchers often use to test their…
pir
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How do you calculate how dense or sparse a dataset is?

I'm looking deeper into collaborative filtering. One really interesting paper is "A Comparative Study of Collaborative Filtering Algorithms" http://arxiv.org/pdf/1205.3193.pdf In order to select which CF algorithm should be used the paper refers to…
djones
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How to model user's buying behavior on Amazon?

For our final course project in Data Science, we proposed the following- Give the Amazon Reviews Dataset, we plan to come up with an algorithm (thats roughly based on Personalized PageRank) that determines a strategic position for placing ads on…
Pavan Manjunath
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