Questions tagged [recommender-system]

Everything related to recommender systems

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AB testing for Recommender models

Let's say that I have two recommendation system models built, Model A and Model B. Now I track the performance of both the models for 5 days from 1st Jan to 5th Jan. Each model has been assigned a ...
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296 views

recommender systems : how to deal with items that change over time?

Let's say I am building a recommender system where items change through time. We suppose that each transaction is composed of : an item $i$ in list of items $(i_1, i_2, i_3, .., i_m)$. a user $u$ in ...
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How to ensure diversity in my recommended ranking?

I have generated a ranked list of items but I want to ensure that the ranking takes care of diversity basis some item metadata. Most of the way I can think of seems computationally expensive. Is there ...
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If we only have the rating scores of items provided by the users, how do we use matrix factorization to build a recommender system model?

If we only have the rating scores of items provided by the users, how do we use matrix factorization (MF), factorization machine (FM), and deep learning (DL) to build a recommender system model?
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30 views

how to calculate similarity between users based on movie ratings

Hi I am working on a movie recommendation system and I have to find alikeness between the main user and other users. For example, the main user watched 3 specific movies and rated them as 8,5,7. A ...
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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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how to evaluate the performance of a recommender system with single recommendation

Say we have a recommender system in production which recommends 1 our of N items according to some internal algorithm f given inputs Xi for each user i, let's assume f is a black box model. We have ...
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Best way to evaluate interlaced recommendation system results while reducing bias

I already asked this question but I worded it in such a way that it was a completely different question to the one I want to ask. I have not deleted the old question in case someone finds it useful. ...
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1answer
578 views

precision@k and recall@k

Normally, I am familiar with precision and recall evaluation metrics but as you know recall@k and precision@k are different things and used in ranking evaluations especially recommendation systems. I ...
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1answer
102 views

A weird result from a recommender system

Say there're the top 10 most popular items among 100 sales products and about 100k users regularly purchase items on daily basis. ...
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12 views

How does Latitude and Longitude be helpful in making the Venues/Places Recommendation system?

I am trying to build a recommendation system which suggest the places on the basis of their ratings , reviews etc . I want to use Latitude and Longitude , but I don't know how it will be helpful in ...
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525 views

What is difference between Nearest Neighbor and KNN?

I was taking the tutorial of making Recommendation system , there I read that Nearest Neighbor is different from KNN classifier . Could anyone explain that what is Nearest Neighbor and how it is ...
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37 views

I need direction for a research project

I am new to machine learning so please bare with me. I'll try to keep this short and sweet. We are building a makeup simulation and recommendation system. My part is to recommend a makeup which is ...
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1answer
438 views

Neural network model for sparse multi-class classifier on Tensorflow

The problem I'm trying to solve is the following: the data is Movielens with N_users=6041 and N_movies=3953, ~1 million ratings. For each user, a vector of size N_movies is defined, and the values ...
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1answer
72 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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1answer
74 views

How to estimate missing values when calculating NDCG

I would like to compare recommendations methods using NDCG metric on MovieLens dataset. In ranking problem, the goal is to rank items based on their relevance for user. Ranking models can be learned ...
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10 views

Methods to generalise NCF recommender systems to unseen users, same set of items?

I'm new to recommendation models, and am starting to build a recommender system on the MovieLens dataset using NCF-style model. As I'm building it I'm wondering if, once trained, I can apply it to my ...
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3answers
2k views

Cosine similarity with arrays contaning NaN

I am trying to calculate a cosine similarity using Python in order to find similar users basing on ratings they have given to movies. As it can be expected there are a lot of NaN values. I am using ...
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2answers
192 views

Which metrics for evaluating a recommender system with implicit data?

I am currently in the process of creating a recommender system. This recommender system works with a neural network and then searches for the closest neighbors and thus gives recommendations for a ...
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1answer
72 views

Recommender system that connect users with each other , should I go for content based or collaborative filtering?

I am trying to build a system where user come on the platform and he chooses a topic(predefined few topics) and then we connect him with any random online user who chooses the same topic. Then they ...
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1answer
111 views

Neural Network - Sparsity of collaborative based filtering and modelling the prediction problem

I'm fairly new to machine learning and for that matter, neural networks, but for the past couple of days I decided to take a stab at a fairly classical and practical problem of neural networks/machine ...
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18 views

How to get KNN linearly hybridised by two similarities?

I'm writing a KNN (collaborative filtering) hybrid similarity recommender and I need some advice. It is based on this paper. I've currently got 2 datasets. The first one is ...
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1answer
61 views

Learning similarity of representations

I am interested in a framework for learning the similarity of different input representations based on some common context. I have looked into word2vec, SVD and other recommender systems, which does ...
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1answer
180 views

exercise 9.3.2 from mmds book

I am reading this book http://infolab.stanford.edu/~ullman/mmds/ch9.pdf there is an exercise 9.3.2 a) it says Exercise 9.3.2 : In this exercise, we cluster items in the matrix of Fig. 9.8. Do the ...
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239 views
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33 views

Can I sum up feature vectors of a user‘s collection?

I want to find items that are similar to items users already have in their collection. Every item has attributes, so I created feature vectors where every element of the vector represents an attribute ...
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1answer
33 views

Cold start recommender system with features

I have to develop a recommender system where most of the users only buy 1 item, so I have a cold-start problem. For this reason, I'm discarding matrix factorization techniques and content-based ...
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1answer
535 views

What's the best classification model for this recommendation engine?

I'm not a data scientist but I'm trying to implement a recommendation engine on my company. My application runs on PHP but I'll use Python to process this data. My company is an online school, with ...
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1answer
240 views

Proper evaluation method for recommendation system with implicit feedback?

I am trying to implement a recommendation system for a live-streaming website. Here "users" are simply the website users and "items" are streamers that they should watch. I ...
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18 views

How metric learning works for content based item retrieval

I was doing some computer vision experiments and recently I have started learning about metric learning and the image retrieval problem. I was experimenting with the inshop image retrieval dataset to ...
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1answer
57 views

Two-tower net does not learn when made deep

I have been trying to train a relatively simple two-tower net for recommendation. I am using PyTorch and the implementation is the following - basically embeddings layers for users and items, optional ...
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8 views

Model performance in different snapshots varying

I am trying to solve this problem. A medical representative needs to visit some doctors' clinics and for that a model will generate probability scores for visiting a clinic. I ma using a tree based ...
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3answers
6k views

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. ...
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1answer
27 views

Calculate implicit rating from streaming behaviour for Recommendation Engine

I have a dataset containing some user streams data for particular videos like below: ...
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3answers
103 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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1answer
72 views

Item-based recommender using K-NN

I'm trying to build an item-based recommender using k-nn. I have a list of items, all of which have some properties (features) in common. ...
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1answer
115 views

Click Through Rate calculation (CTR) calculation problem

So I'm doing a use case for a company interview and one of the questions is to calculate the CTR for a sorting algorithm. My question would be: Should I remove the operations where there were no ...
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1answer
22 views

Changing behaviour of an ML model

I am trying to create a ranking system for recommending books to an user. Let's suppose we have some subjects of books like 'A', 'B', 'C', 'D' and from the past behaviour, it is observed that the user ...
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1answer
23 views

Integer encoding and weighing when one feature consists of more names [closed]

Hello I am trying to make a content based movie recommendation system and one feature is genre of the movie. I will give an integer number to each genre randomly. However, some movies are of more than ...
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1answer
890 views

how to build word2vec content based recommendation?

I am building a content-based recommendation system for hotel accommodation. I have a hotel name, hotel description and location. I combined hotel name, description and location. Then, applied NLP and ...
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24 views

What is the right approach to bucket users for algorithms with different coverage for A/B testing

I've couple of recommendation algorithms that I want to A/B test. Algorithm A has 90% user coverage and algorithm B has 95% user coverage. That means if the algorithms are asked to provide ...
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1answer
22 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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60 views

LightFM implementation for scala/java on spark

I am looking for hybrid recommendation libraries such as lightfm that I can use on Spark (with Scala). Any alternative? Or best would be for me to build a hybrid recommendation system on spark's mllib ...
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37 views

Time aware recommender system

I plan to design a recommendation system, especially with Scikit-Surprise. A bit of background: I want to recommend products to shop for. Here, the user is the shop and the items are products (water,...
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1answer
61 views

How to develop Top-N recommendation for evaluating my system

I want to evaluate my recommender system with the Top-N recommendation method and I have a problem. In some situations, e.g. N = 5, I don't have 5 items for listing and I cannot do that for evaluating....
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1answer
1k views

Is there an overview over recommender system architectures?

I want to learn more about the recommender system topic. I am very interested in the usage of different database systems for this use case. My problem is that I cannot find a good overview of ...
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1answer
36 views

Item-to-Item recommendation using DNN

I am new to DNN still learning, have a need to build item-to-item content based recommendation using DNN. For example, say I have a column of strings where each row represents a document I need to ...
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0answers
63 views

Cross validation for Collaborative filter-based recommendation systems

I am an absolute beginner and am trying to implement collaborative filter for furniture ecommerce (think wayfair). I need some guidance about cross-validation strategy. Situation: I am working on a ...
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0answers
32 views

How does an autoencoder 'fill in the blanks' in the context of a recommender system?

My understanding is that an autoencoder takes an input, produces a lower dimensional representation of the input, which should explain the original features in the dataset, and then reconstructs the ...
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1answer
74 views

Temporal train test split for recommender systems

When evaluating a collaborative filtering recommender system, it is practical to split the data temporally. However, by doing so, some users might be present in only either of the train or test set. ...

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