Questions tagged [recommender-system]
Everything related to recommender systems
348
questions
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7 views
How to include user features in a recommender system?
I'm novice in that matter but I was thinking about the formulation of a recommender system. Let's take the example of a movie recommendation system. We have a column dedicated to movies ID (or names), ...
-3
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1answer
20 views
Should I use Machine learning to predict song features for music recommendation? [closed]
I would like to build a music recommendation system which works by analysing the raw audio features of songs grouped in playlists or listening histories to attempt to predict the audio features which ...
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7 views
Get latest Item by Date for a Recommender System
I am building a Recommender System where I am giving the User 3 Recommendations depending upon for the Webpage he is on. Let's say My model gives me 3 Recommendations from 2020, 2019, 2015. I would ...
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13 views
Classify Spanish Text into different Categories
I want to recommend articles to users depending upon what type of article is user reading, Music, Movies, Politics, etc.
I have 3 features: Page Title, Labels, article content.
I am using an API (...
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1answer
19 views
How to filter Items in Recommender Systems?
I have a Recommender System which recommends Articles based on Similarity from 3 Features, "Page-Title, Article Content, Tags". But some of the Articles are NSFW(Related to Adult Topics). I ...
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11 views
What are the Objectives for Recommendation Systems and what Key Results should a Recommendation System focus on?
I know that a Recommendation system helps in the engagement of the users and helps users find more relevant content but I am in search of more complex objectives and key results with regards to ...
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8 views
Link Recommendation System
I am trying to build a Recommendation system on my website for recommending similar articles to the user. Eg: Lets say a user is reading an article about sports on a news website. The next article ...
0
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1answer
25 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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17 views
Recommend System AB test metric events
I build personal recomendation system for choosing games. In website on main page on special place there is collection of personal games recomendation. And after AB test(between 2 recommend system) I ...
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22 views
Building a content-based recommendation system using products' metadata as features?
I am currently working on an apparel recommendation system, where I have tabulated data containing a list of products with their respective metadata (brand, category, color etc.)
I have an additional ...
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0answers
19 views
Can previous successful actions be used as input to policy model in contextual bandits?
In a recommender application, I apply contextual bandits using logged propensity scores similar to this.
The model is retrained daily.
The application recommends images on an e-commerce website. Each ...
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7 views
Can I use LSI (Latent Semantic indexing) to get similar docs for several documents at the same time?
I'm working on a Recommander system in which I'm using LSI to get similarities between videos.
I wonder if I can provide to LSI matrix more than one document and get similar docs for all those. In the ...
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33 views
Data augmentation for recommendation systems
I have a user-item matrix that I use to train a denoising autoencoder to predict the top-k items to recommend to the different users.
The idea is to corrupt the matrix by erasing a percentage ...
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0answers
14 views
Machine Learning Recommender high data intensity
We are building a recommender engine to be integrated in an app that, each time an API is called, will pull thousands of records from an Azure SQL database and create recommendations. Currently with ...
1
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1answer
50 views
How do I build a recommend system based on user's past purchases?
I am exploring approaches to build a model that shows personalized search results (with or without query) for a fashion eCommerce platform. For that I am first working on coming up with a bunch of ...
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0answers
40 views
User-Item based Recommendation system with data containing binary data
I have a data set which contains about 400,000 unique items present on a platform. The users on this platform can like and save this in their own list. Now, I have about 4000 users with their like ...
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2answers
26 views
How to identify text similarity based on training data?
I have a set of documents (1 to 11) for which the labeling is done.
Lets Assume:
...
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0answers
25 views
Predicting Item Ratings with the Log Likelihood Ratio
I'm trying to infer prediction ratings from an item-item similarity matrix where the similarity score is calculated via the log-likelihood ratio (LLR). I'm using this code snippet to calculate the LLR ...
0
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1answer
20 views
How to calculate similarity between 2 users based on the images they share?
Say there are 2 users, A and B, and they each shared 10 images (in some social media site), which I have collected in 2 folders separately.
I want to calculate the similarity between the 2 users based ...
0
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1answer
32 views
Personalized Search based on client's purchase history and product preferences!
I am exploring approaches to build a model that shows personalized search results (with or without query) for a fashion eCommerce platform. The data that I have are:
Client's purchase history i.e the ...
1
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0answers
15 views
How to use the position factor in known data as a feature in recommendation surfacing?
The problem is recommending stories on a website, just below each story based on how similar the stories are and some historic data based on what recommended stories were clicked or not clicked. So ...
2
votes
1answer
49 views
How to build recommendation model based on resume and job description?
How to build a model which will result in better recommendation of resumes based on the job description given?
I am familiar with bow or tfidf (n-grams) approach and then take a cosine similarity but ...
2
votes
1answer
35 views
Should you cluster before performing collaborative filtering?
So I am building a recommendation model using customer and product information. This will be done via implicit, that is, a customer has a product or not as we don't have rating information about ...
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33 views
How to train a recommender system to improve the customer class?
Considering the definition of a recommending system
A recommender system, is a subclass of information filtering system that seeks to predict the "rating" or "preference" a user ...
1
vote
1answer
62 views
How do I predict a set of frequently bought items?
I have a dataset of retail transactions wherein different users buy certain items together. For example, a user A buys a toothpaste, a toothbrush and a floss at the same time, and a user B buys a ...
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0answers
10 views
Perform collaborative recommender analysis without rating in a transactional data
I'm exploring options for recommender systems optimized for the online retail dataset, which would take into account that no product or user rating is available. Can collaborative recommender analysis ...
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0answers
40 views
How to calculate latent vector for a user in ALS based on some new input?
So I have an ALS trained in pyspark but then I get some interactions from a new user that wasn't in the training set. I want to give recommendations to that new user without retraining the ALS based ...
3
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2answers
158 views
How to use hashing trick with field-aware factorization machines
Field-aware factorization machines (FFM) have proved to be useful in click-through rate prediction tasks. One of their strengths comes from the hashing trick (feature hashing).
When one uses hashing ...
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0answers
16 views
Approaches For Recommender System Using Complicated Novel Dataset
I have a question about the best approach(s) I should take in building a recommender system for a project I'm working on.
I have created a dataset. The dataset has the following:
400,000 users
For ...
0
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1answer
45 views
BPR TripletLoss Recommender System
I am trying to modify the code of this repo to build a recommender system based on BPR triplet loss.
In particular I modified the TripletLoss layer class like this
...
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0answers
12 views
News Recommendation Engine with XGBoost
I want to build a news recommendation engine with XGBoost, but the data I have contains implicit user ratings, view history of a user. I know what my X's will(user embeddings + Item Embeddings) be but ...
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1answer
39 views
Learning Resources for Recommendation system
Beginner here:
Could you please suggest some of the learning resources (books/youtube/articles) for beginners who want to build a recommendation system for their organization.
Have no clue about it ...
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0answers
58 views
KNN() and SVD() for recommender system
I come here cause I have some troubles (or is it normal ?) with the rating predicted by
SVD() and KNNWithMeans(), I'm using the Sckit-Surprise library . Here is context :
I have 637 069 rating
I ...
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0answers
14 views
Is there an experimental section for product recommendations?
We already know that the recommendation engines are trained on basis of several factors and they come up with Top N best product recommendations. For eg: The Netflix Top N Video Ranker.
Now, my ...
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0answers
18 views
Recommendation system with active learning
I have data where companies ask users to score a bunch of questions but some items may be randomly chosen while others are personalized. Users score higher in personalized questions on average. I have ...
0
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1answer
146 views
How to train-test split and cross validate in Surprise?
I wrote the following code below which works:
...
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0answers
6 views
When is sparsity becoming a problem when building recommender system?
When building a recommender system the rating matrix is usually quite sparse. Sparse means that such a matrix contains mostly empty values (or 0s for that matter, although these could also be ...
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18 views
How to obtain 5 star rating predictions from content-based filtering
I am attempting to compare multiple recommender system approaches, including content-based filtering and collaborative filtering. My plan is to predict 5 star ratings and use MAE and RMSE as metrics ...
0
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1answer
36 views
Building a content-based music recommendation system
I am trying to build a recommendation system in Python that recommends songs based on a playlist.
What I have is two datasets:
1. One dataset consists of 350 songs from my playlist and 13 acoustic ...
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0answers
23 views
ML recommendation system with items organized in a tree
I would like to develop a recommendation system (probably hybrid, user-based and feature-based) for items which are organized in a tree (there are categories, divided in sub-categories, divided in sub-...
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130 views
System Requirement to train BERT model
How much Hardware is required to train it well?(My current PC specs: 8GB RAM, i5 2 core Processor, Standard GPU (No work going on GPU))
I have a dataset of approx 1lakh records.Is it is necessary to ...
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106 views
How to create a model and make predictions with LightFM?
I've been researching on how to develop a hybrid recommender system for a simple book dataset, the main goal is to use both explicit data (purchases) and latent factors (features) to make the ...
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0answers
9 views
Manipulating the relative weight of tokens inside CountVectorizer
This is transparently a classic IMDB data recommender question. I'm trying to build a recommender system that suggests movies that a user is likely to enjoy. If I have my terminology correct I am ...
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0answers
19 views
Training a cosine similarity matrix for similar text recommendation
I'm working on similar movie names recommender system.
I have a dataset of only movie_titles that I converted into matrix using tfidf and then computed the cosine ...
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0answers
15 views
Ranking graph's nodes by score propagation
Problem
I have the following directed tripartite graph $G(E\cup V\cup P, A)$, where there is a many-to-one symmetric relationship between the subsets V and E - $e\in E,v\in V,[e, v]\in A \iff [v, e]\...
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162 views
Recommender System Web Application
First of all I apologize if posting such thing is against the rules here, but I did a Google research, and actually did lots of it, however couldn't get the answer I wanted and wouldn't know where to ...
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0answers
16 views
How to make a popularity-based recommender system having data on posts and number of likes? Please review a code
I'm writing a popularity-based recommendation system, where I have data on posts and likes the posts have. I need to recommend posts to a user based on their popularity (obtained likes).
Packages and ...
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0answers
11 views
Factorization Machines with some some pairwaise effects and some linear effects
I have some covariates $x_1$, $x_2$, $x_3$, .., $x_{10}$. I want a linear term for all these covariates and a pairwise effect for $x_1$ and $x_2$, and I do not want any other pairwise effect. Is there ...
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15 views
Upsell project based on sales records
in my company we are working on a upset project in which we are trying to solve the following problem:
What we propose to our customer that he/she may be interested in based on the fact that he/she ...
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0answers
15 views
How effective would this pseudo-LDA2Vec implementation be?
For my site I'm working on a chat recommender that would recommend chats to users. Each chat has a title and description and my corpus is composed of many of these title and description documents. I ...
