Questions tagged [recommender-system]

For questions related to recommender systems in the context of machine learning and data mining.

22 questions with no upvoted or accepted answers
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How matrix factorization helps with recommendations when it converges to the initial user-items matrix?

We can say that matrix factorization of a matrix $R$, in general, is finding two matrices $P$ and $Q$ such that $R \approx P.Q^{T}$ with some constraints on $P$ and $Q$. Looking at some matrix ...
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19 views

How to model personalized threshold problem with machine learning

Assume that I have a candidate selection system to generate product/user pairs for recommendation. Currently, in order to hold a quality bar for the recommended product, we trained a model to optimize ...
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88 views

Which machine learning algorithms can be used to build a recommendation system?

I am working on building a recommendation engine. I need to build a model that recommends similar items. Currently, I am using the Nearest Neighbor algorithm present in ...
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1answer
107 views

What are some limitations of using Collaborative Deep learning for Recommender systems?

Recently I worked on a paper by Hao Wang, Collaborative Deep learning for Recommender Systems; which uses a two way tightly coupled method, Collaborative filtering for Item correlation and Stacked ...
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25 views

A recommender system based on millions of fields including text and number

I want to train a model based on millions of fields, including text and number, that are stored in a SQL database and recommend a perfect match based on some inputs. Now, which algorithm is the best ...
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15 views

Hyperparameters for Reproducing the Results of IRGAN on MovieLens 1M

I am trying to reproduce results reported for IRGAN (information retrieval GAN) on the MovieLens 1M dataset. The results I want to reproduce and their sources are listed in the table below. Model ...
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11 views

Choosing the size of the network for Neural Collaborative Filtering (NCF)?

I've been working on Neural Collaborative Filtering (NCF) recently to build a recommender system. After doing some hyperparameter tuning with various sizes for embedding and dense layers sizes, from ...
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40 views

How to change the number of input neurons in embedding layer?

I was building a recommender system using Tensorflow recommenders (TFRS) library . I was following the official tutorial for ranking model , where they have used two-tower model. The part where I have ...
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22 views

what is the correct approach for KNN in item based recommendation system?

if I make an application for movies and each user in the system can rate the movies. And I want to make a recommendation system to recommend movies to active user based on his rating for other movies. ...
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19 views

Human intuition behind SVD in case of recommendation system

This does not answer my question. I struggled very hard to understand the SVD from a linear-algebra point of view. But in some cases I failed to connect the dots. So, I started to see all the ...
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82 views

Why can't I Hyper tune my KNNBasic Algorithm?

I've been trying to hyper tuning my KNNBasic algorithm by the help of grid search for recommendation system for movie review data. The problem is that both of my KNNBasicTuned and KNNBasicUntuned ...
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Anyone familiar with Bilateral Recommendation System? And suggest any related papers?

I'm working on Bilateral Recommendation System. But not able to find much related papers. Could anyone suggest any papers relative? Thanks
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Reducing the Number of Training Samples for collaborative filtering in recommender systems

I have the following problem: I am doing some research on the accuracy of recommender algorithms that are mostly used nowadays. So, one way to measure their performance is by checking how well they ...
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23 views

Estimating Baselines using ALS

I am trying to figure out how ALS works when minimizing the following formula: $\\ \\$ $\text{min}_{\lbrace b_u,b_i \rbrace} \sum_{(u,i)\in \mathcal{K}} (r_{ui} - \bar{r} - b_u - b_i )^2 + \lambda_{...
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61 views

How do stacked denoising autoencoders work

I've been studying a recommender system which uses a collaborative deep learning approach and Bayesian learning. It has the following NN representation : I need to know the working of stacked ...
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1answer
27 views

Recent methods for Decision Support System (DSS)

In Decision Support System (DSS), we rank items based on predetermined weighted criteria. For example, we want to rank prospective programmers based on their working experience, required salary, set ...
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17 views

Why use two different embeddings for actions in this paper?

I was reading this paper Top-𝐾 Off-Policy Correction for a REINFORCE Recommender System and I'm wondering is there a particular advantage to use different embeddings for actions, one embedding is ...
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Recommendation and prediction system for learning performance of students

I would like to start my master's thesis soon. The topic is "the use of collaborative filtering for creating recommendations and predictions of learning performance". I have a dataset that ...
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17 views

How to use Tensorflow Recommenders' Retrieval task with Keras data generators

I've recently started working with the package to build recommender systems, and so far, I've successfully built a Ranking task that takes the inputs from a Keras Data Generator. However, I could not ...
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57 views

How to use Product Matching to create Product Bundles

I am working on a product matching model. GOAL A store has many products like creams, perfumes, other beauty products. Based on product properties I have to create bundles of it so we can sell more ...
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19 views

How can I find the optimal K for K-nearest neighbor Algorithm

I want to know what is the best way to find the most suitable k in knn algorithm for Item-based collaborative filtering . I want to make a recommendation system for an application to recommend the ...
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41 views

How can I build a recommendation system that takes into account some constraints or the context?

I am building a recommendation system that recommends relevant articles to the user. I am doing this using simple similarity-based techniques (with the Jaccard similarity) using as features the page ...