Questions tagged [recommender-system]

Everything related to recommender systems

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Recommending college degrees based on high school subjects

I have a list of our college students' high school courses. I want to recommend college degrees to current high school students based on their courses - that is, predict a class based on a vector. ...
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20 views

The best ML algorithm to give recommendations to fill in a selection

I have a ML problem where I want to suggest a combination of options to the user based on their current choice of options. The options are all boolean (selected or not selected), there are several ...
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Test dataset contains invalid data. ( Error 0018 ) in Azure ML Studio Evaluate Recommender

I am doing a crop recommender system using the Matchbox recommender system in Azure ml studio. while splitting the dataset using Recommender split, it won't be split. but I split while using split ...
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9 views

Recsim for Movie recommendation

I was reading through Recsim Is there a simple implementation of this - On MovieLens data for example? My understanding so far - The UserModel is for modelling and sampling users - based on user ...
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5 views

Mutiple binary classification for for best propensity to buy one of the product

Problem:- I have 5 products for sell and I can pitch only one product in a month to one customer.so I wants to know which product customer can buy. Proposed solution:- I build 5 binary logistic models ...
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9 views

Suggestions re best approach for the task: recommender systems, contextual bandits, classification,

The task is about choosing the best compensation option for a customer. A customer (features: regular/premium, old/new, etc ...) which is facing a certain type of an issue such as delayed order (...
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15 views

Tensorflow Keras predicting one-hot-vectors

I am trying to build a recommender predicting products. The inputs are one-hot encoded product IDs, and so is the output. (0, 0, 1, 0) to (1, 0, 0, 0) There are 83 unique IDs in the first category and ...
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20 views

Ranking recommendation system

I have problem with construction recommended system. I have a DataFrame with columns of users , items (books) and the order in users read the book - ...
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14 views

Instagram Profile Similarity Features

I want to find similar IG accounts in a semantic way(not demografic like fan count, language, country,...) and thought of the following features: Post Text Similarity (Embeddings by SBERT, averaging ...
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1answer
14 views

Do I need to read an entire database for a recommendation system?

Let's say I have a database with approx 100000 rows. I want to build a content-based recommendation system. Do I really need to read the entire database to calculate similarity? That would be very ...
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11 views

How to explain rescaled recommendation scores to end-user?

I constructed a recommendation system based on both Boolean and linear features that present products to potential buyers. The raw scores are not easily digestible for humans (i.e. the highest score ...
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10 views

Building a recommendation system with a graph database

When I'm reading about building recommendation systems with collaborative filtering and they generally don't talk about graph databases like neo4j. Are graph databases enough to implement the best ...
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21 views

What are good resources to learn KNN text classification using Tensorflow?

I found the KNN image classification tutorial using MNIST dataset and was able to lear how it's working. Are there any resources that describe to apply the same KNN algorithm to text classification. I ...
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26 views

How to incorporate multi-task in CTR/recommendation model (deep & wide/ xDeepFM etc)?

I am building a rank algorithm for an e-commerce website that ranks the product based on likely hood of purchase and I have formulated this problem into a binary classification problem. Given each ...
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40 views

Recommender System with Time as the dependent variable and not ratings

I'm currently designing a recommender system in watching videos (all with same duration). I have the user_id and the video_id and I have the data for users's watch duration for the video_id. I ...
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11 views

Recommender system for matching user input keywords to objects that have different keywords assigned to them (and getting the matching weights)

I'm looking for some tips in the right direction as to what to look into for this recommender system: We have a predefined set of objects, each with a few keywords assigned to them. We can call the ...
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31 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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1answer
46 views

Change feature importance in a trained model

I am giving a toy example for describing a real world business problem. Let's say I am a publisher and I have some book stores to visit. By visiting those stores I will check whether they have ...
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36 views

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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12 views

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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11 views

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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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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9 views

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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31 views

Best approach for A/B testing two different recommendation systems

I have two recommendation systems for musical preference that make a list of predictions for a particular user based on the songs they have saved in their library. The user then rates how good each ...
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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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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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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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19 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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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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26 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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79 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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14 views

Neural Recommendation System - Explanation

Hello I am working on a recommendation problem in which I want to recommend the next best product to a customer. I am using a collaborative filtering approach but I would like to have as a result, the ...
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50 views

Weighting of features in Recommender Systems

I'm new to Recommender Systems, and wanted to figure some things out in order to make the best possible Content Ranking System. I want to make a ranking of all the content (and content providers) ...
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23 views

Can latent factor model work for new users?

I am studying latent factor model for recommendor system. It does matrix factorization(like SVD) on the user-item rating matrix. What I am not sure is, does a trained model work for a new user that is ...
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14 views

estimate user's satisfaction of a video based on how much of it they watched - normalization

I am trying to estimate how much a user liked a video using how much of the video they watched. Let's say, on the scale of 1 to 10, 1 means that the user didn't like it at all, and 10 means they ...
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7 views

How is SVD from scikit-surprise handles empty values

I am studying the surprise lib for recommender system. SVD from this lib doesn't require all value input in user-item matrix. But it is a must of the original SVD method. The official doc doesn't ...
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11 views

Top n products as a kind of recommendation system

I'm looking for a paper, book or something similar that describes only the top products as a kind of recommendation in a recommender system. The top products can be determined with a simple counter. ...
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14 views

Why I need to generate train instances and load negative samples?

If you look at this GitHub link ( here is the paper link for the implementation ) you can see that the get_train_instances method generates trainingns instances. In ...
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1answer
95 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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12 views

Adding additional information in content-based recommendations

I have a book dataset where 100 users have rated the books as like/dislike. Each observation with features Table1 : ['user_id','book_name', 'book_genre','author','date_published','like/dislike'] These ...
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22 views

product recommendation of a single product based on customer similarity?

I have been wondering how you can build a model to recommend only one single product to a bunch of customers. So basically the question that I would like to answer with this model is to have a ranking ...
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28 views

Learning to Rank vs Reinforcement Learning in Information Retrieval - which one is preferable and why?

I am trying to create an information retrieval system which can benefit from user feedback (either implicit, through e.g., click-through data) or explicit (e.g., binary feedback on irrelevant ...
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8 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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22 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
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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255 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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1answer
920 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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1answer
186 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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1answer
77 views

When to stop showing content on recommendation engines?

Let's take an example. I log into my Netflix account and see that it's suggesting the show Friends to me. But I have no interest in watching Friends. So I ignore it. The next time I login, it suggests ...
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41 views

Document matching with more priority to certain features than others

I am working on recommendation systems wherein I need to match the similarity of 2 users. Now, I know that I can use Tfidf vectorizer to calculate the the cosine similarity score between them. But, ...