Questions tagged [recommender-system]

Everything related to recommender systems

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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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10 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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14 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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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 ...
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34 views

Combine features in Machine Learning KNN

I'm trying to build a simple book recommendation system, where I don't have any kind of ratings (no comments, no likes, no 1-5 stars, ...). The information I can use is the following: Book metadata ...
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21 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. Here, the user is the shop and the items are products (water, ...
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1answer
14 views

Call routing using AI

I'm trying to find out how AI can help with efficient customer service, in fact call routing to the right agent. My usecase is given context of a query from a customer and agents' expertise, how can ...
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Offline evaluation of recommender systems

Let's say I want to compare whether one recommender system (A) is better than the other (B). One approach is to let people rate recommendations returned by both systems. However, there situations ...
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160 views

Building a tag-based recommendation engine given a set of user tags?

Basically, the idea is to have users following tags on the site, so each users has a set of tags they are following. And then there is a document collection where each document in the collection has a ...
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1answer
31 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
35 views

Recommendations based on other products seen

I am trying to develop a basic book recommender system to get in touch with the field and start learning methods and how to prepare the data. The Dataframe I am using is pretty plain, it has the ...
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42 views

Building a recommender system [closed]

I want to build a recommender system for shops, where I recommend items. I've learned about these systems like with content-based, collaborative filtering and so on. But now I want to make one on a ...
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1answer
45 views

In recommender systems, how to avoid recommending a product that the user has just bought?

Suppose I'm running an online store that sells many products, but from only a couple of categories, say: $A$, $B$, or $C$. Let's say a user has bought a product in the A category, and there's no ...
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51 views

Deal with huge amount of data

I'm writing to get advices about my project. I want to make recommander system for shop with some products. In fact i want to recommand to shop A to take item X because shop B sell this item and ...
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12 views

Recommendation Engine - Content based and Collaborative recommendation?

I am building a recommendation system for hotel accommodation. I scraped data from online booking portal and now my data has Name of the hotel, review, description and location. I built a simple ...
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19 views

Learn recommendations from dataset

I have a corpus of news articles and 6 annotations indicating whether a pair of documents are related or not. Not all possible pairs are annotated. Since a vectorised representation can find out the ...
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20 views

Code freezes and never returns when linear_kernel (sklearn.metrics.pairwise) is used on 20M Movielens dataset

I'm fairly new to ML/AI, i'm trying learn the content based recommendation - here is my source code - https://github.com/jaganlal/content-based-recommender I'm using MovieLens 20M dataset - tags.csv ...
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1answer
17 views

Recommender system that matches similar customers with similar highly rated products?

I have a dataset of 1,000 customers that bought 20 distinct phones and rated them 1-5. I have several demographic attributes for these customers (gender, age). My website offers 100 distinct devices, ...
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1answer
45 views

NCF Recommender- The target encoded within the model input, why doesn't it overfit easily?

In the recommender system NCF, the input is a batch of user-item interactions (one-hot encoded) and the output is a 0-1 score of whether the item has been bought or not: This seems to indicate that ...
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1answer
99 views

Train-Test split for a recommender system

In all implementations of recommender systems I've seen so far, the train-test split is performed in this manner: ...
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76 views

Multidimensional collaborative filtering model

I have a dataset that is approximately structured in the following way: 500 users, 500 products, 100 countries, 2 seasons, 300000 ratings. Meaning that I have 300,000 rows containing unique ...
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What public datasets exist for content-based recommendation? (e.g. News Recommendation)

I'm an AI Master student working on my Thesis. My research focuses on content-based User Modelling in Recommendation. More specifically, I'm aiming at improving methods of User Modelling to cover more ...
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26 views

Operations on Recommendation Embeddings

I've trained a recommendation system to recommend steam games based on game tags. An example output is shown below, where GAME is the game recommended based on the <...
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31 views

How to use ndcg metric for binary relevance

I am working on a ranking problem to predict the right single document based on the user query and use the NDCG metric to measure the model. Given the details : Queries ( Q ), Result Document ( D ),...
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1answer
31 views

Calculate Similarity using User's Personal Data?

I want to find out which users are similar to each other using their personal/organisational data, such as department, company, site, etc. I have this data in a boolean format, as shown below: ...
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2answers
75 views

How to calculate precision at K and NDCG for ranking algorithms

I am ranking a filtered item list as per user's metadata and historical behaviour. Now how to calculate metrices like precision at K? One approach could be - Divide historical data in training and ...
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How to evaluate a content recommendation model unsupervised (unlabeled dataset)?

I have a lot of unlabeled data which is crawled from job listings and I'm trying to build a content based recommendation model. I just need if someone could help me out on how to evaluate such model. ...
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15 views

clustering changing Label

I have dataset with clustering label (this label is the group of each point) and I want to create such recommendation system or any other model to help the point for changing his group (for example ...
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1answer
26 views

CV(Curriculum vitae) Recommendation System guidance

I am building a recommender system which matches people's CV with a vacancy. So far, I used TF-IDF & Cosine Similarity to get a matching score between a vacancy and a candidate's CV. I want to ...
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1answer
66 views

Calculating Rank Ordering Error Metric for implicit recommendation

I'm reading Collaborative Filtering for Implicit Feedback Datasets. On page 6 they detail their evaluation strategy, which they define as mean Expected Percentile Ranking with the following formula: $...
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1answer
66 views

Can a recommendation system be used as a binary classifier?

I have a computer-generated music project, and I'd like to classify short passages of music as "good" or "bad" via machine learning. I won't have a large training set. I'll start by generating 500 ...
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1answer
59 views

Evaluating the performance of a machine learned recommendation system

I have a set of resumes $R=\{{r_1,...,r_n\}}$, which I've transformed to a vector space using TF-IDF. Each resume has a label, which is the name of their current employer. Each of these labels comes ...
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71 views

Examples of the use of xgboost for recommender systems?

Are there any state-of-the-art implementations of xgboost in recommender systems? I'm looking for GitHub implementations but also papers that discuss this. I've only found this paper https://...
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1answer
34 views

Using Amazon Personalize to build a Recommendation System

I would like to build a recommendation system based only in the items metadata. I have an input vector with some desirable topics that the user want to read about, for example: (self-help, yoga, ...
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9 views

how to use user KPI score data for making recommendations based on improving the performance

I have a dataset with these data points: user_id login_points meeting_complete points meeting_missed_points call_points lead_created_points and some features which tells the user activity and ...
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7 views

Time series modeling with unknown sampling times

My problem is building a recommendation engine, where actions should lead to desired range of states. A state is measured by a sensor - one continuous feature. An action is measured by a different ...
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565 views

How to calculate NDCG in recommendation system

This is a question about NDCG, which is a recommendation evaluation metric. The following are being used as evaluation indicators for recommendations. $$DCG = r_1 + \sum\limits_{i=2}^{N}\frac{r_i}{...
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2answers
40 views

How to encode an array of categories to feed into sklearn

I'm working on a recommendation problem, broadly following the Youtube paper on theirs. Their surrogate problem is to recommend the next video a user will watch. One feature they include in their ...
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1answer
27 views

Value error in an embedding layer

I am new to deep learning and I am trying to build a book recommender system using embedding layers. I use one layer for the book and one for the user. I am having trouble with fitting the model. ...
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1answer
47 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
426 views

How to draw neural network diagrams with this particular style?

I would like to draw a neural network architecture with the follow style. Do you know which tool can be used to do this? The paper is Operation-aware Neural Networks for User Response Prediction.
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31 views

nDCG - choose relevance scores

I am evaluating a recommender system using nDCG. The recommender system predicts similar movies for a given movie. I want to evaluate predicted similarity rankings by comparing them to a ground truth ...
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35 views

Understanding reduced dimension embedding from tabular data

Background I am working on building a collaborative filtering recommender system in Keras for a school project, following an approach from this article. The approach is to take tabular user, item ...
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1answer
175 views

TS-SS and Cosine similarity among text documents using TF-IDF in Python

A common way of calculating the cosine similarity between text based documents is to calculate tf-idf and then calculating the linear kernel of the tf-idf matrix. TF-IDF matrix is calculated using ...
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1answer
30 views

On the offline evalution of recommender system

There are mainly three ways to evaluate a recommender system: offline, online and user study. For most academic papers, offline evaluation is used to show the improvements: They split the offline ...
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9 views

play session from ratings dataset in Movie20 M

I need to extract listening sessions from the ratings dataset which has the columns cols = [userId movieId rating timestamp] timestamp is just a number for eg 1112486027 listening sessions are ...
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22 views

Recommender system heavily biased towards popular items

I am training a pure collaborative filtering recommender system on MovieLens 1M using Tensorflow-Ranking. I use embeddings to represent users and items and feed concatenated embeddings through two ...
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10 views

How to validate collaborative filtering recommender system in r?

I have a project which I have to make a recommender system of BX Books dataset. I use cosine similarity as my algorithm. I came up with this script of R: ...
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1answer
228 views

Understanding the softmax output in Youtube's recommender

This question has been asked before, but never (that I can see) satisfactorily answered. I'm reading Youtube's paper on their recommender system. The system has two elements, the first of which is a ...
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22 views

Transfer Learning and Recommender Systems

I have a task in which I am pretending to have an "unobserved" system, let's call it the target system, that I am using an LSTM from a similar system that has observations to perform the regression. I ...

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