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Questions tagged [recommender-system]

Everything related to recommender systems

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139 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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1answer
67 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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64 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 ...
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19 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 ...
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0answers
38 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 ...
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410 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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0answers
36 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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0answers
23 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
14 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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0answers
22 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
56 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 ...
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0answers
78 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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0answers
34 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
32 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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1answer
52 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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0answers
56 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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1answer
45 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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1answer
43 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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1answer
309 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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0answers
45 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 and ...
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1answer
98 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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0answers
29 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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0answers
87 views

How to perform Learning to Rank for a small dataset

I am very interested in applying Learning to rank to my problem doamin. When I read through the literature of Learning to rank I ...
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0answers
43 views

Reducing the Number of Training Samples for collaborative filtering 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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0answers
80 views

What is the current state of the art solution for Movielens 100k / 20M?

I found Basic recommendation system for Movilens dataset using Keras which has a solution which works ok (MAE 0.84). What is the current state of the art for this dataset?
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44 views

How can you recommend songs based on a user's past listening history by genre (content filtering)?

I'm interested in getting a user's past listening history from Spotify (API call to recently played) and being able to suggest songs from the Charts (another API call for current chat listings) that a ...
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0answers
21 views

Personalised search ranking for hotels

I've built hotel embeddings which gives very satisfactory results in returning similar hotels for each hotel. Now the problem I'm trying to solve is to rank the hotels in order of relevancy to the ...
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0answers
50 views

Is it a good idea to train Neural Network for classification on dataset where each document has a different class i.e. no class is repeated again?

My goal is to build a recommendation model for which I want to use Neural Network (LSTM). The user will give some input keywords and the model should return the suggestions (classes) based on ...
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1answer
26 views

How do I recommend items to out of training users based on its recent views?

I used Spark's ALS implementation of matrix factorization (Collaborative Filtering for Implicit Feedback) to train user and item embeddings. Since we have a lot of users in system, I had to sample ...
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1answer
99 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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2answers
53 views

How do I correctly build model on given data to predict target parameter?

I have some dataset which contains different paramteres and data.head() looks like this Applied some preprocessing and performed Feature ranking - ...
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0answers
22 views

recommend new category paths based on factor item matrix and sales of the items

Matrix A be a user item matrix. Upon performing UV decomposition, I have just the V matrix. The matrix A differs every week and I get a new V matrix every week. The matrix U is not kept track of and ...
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0answers
29 views

Including user-item pairs without interactions in implicit feedback dataset for recommender system

I have a dataset which contains information about how many times a particular user viewed certain item. So, I don't have rows for all combinations (where the value will be zero ofc because the user ...
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0answers
120 views

Job Recommendation System

I am building a Job Recommendation System where I have Student Data for different subjects in Machine Learning(Data Viz, Python, Statistics, etc) and their skills from the resume. Need to Recommend ...
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1answer
53 views

Creating a Feature to determine popularity

I am building a recommendation system where I have multiple categories. I would like to Know how popular a product is in each category. For that, I am considering probability as one factor. For ...
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0answers
16 views

How do I store/model data needed for my recommendation module?

I'm reading data from a store's product catalog, a 100mb xml file which contains product-wise attributes like prices, categories, etc. Given a product_id, my job ...
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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
527 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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0answers
34 views

What Algorithm to use for course path

If I want to suggest a course path for a student who wanted to be a chemical engineering where each degree has to go through certain mandatory courses like math ,physics chemistry . Again to complete ...
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0answers
44 views

Multiple Seeds Content Based filtering Recommender System

I want to create a content based filtering recommender system which has multiple seeds. All that I have read about is having an initial seed from which the recommendations should be similar to. This ...
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0answers
23 views

Recommender system: Give a feature more significance than another

I am trying to build a recommender system that predicts hotel prices based on a great number of features. I have a column representing the hotel rating out of 5 and another column indicating the ...
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0answers
78 views

Initialize a recommender system with no dataset

Consider a platform for content recommendation based on the user history. The contents are books and articles and by history I mean what the user has read, what he has shared and so on. I know that ...
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2answers
141 views

Reduce data length to train effectively

I have customer buying data with each row specifying an item bought by customer. The problem is that even if at the same time customer buys five items then there are five different rows for it and as ...
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0answers
86 views

Recommender algorithm

We have some skill levels (beginner, advance, expert) which users assign themselves. Then they get some rating (2, 3, 4, 5) stars from others…. So an expert may have 2-star overall rating and an ...
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0answers
150 views

Tensor Decomposition for Higher-Order Context-Aware Recommender Systems

Let me motivate my problem with an example. Let's assume our observations concern ratings a user give to different items, while navigating through item catalog. The user begins rating item1 (may be ...
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0answers
597 views

Recommender system based on binary likes/disklikes?

I am building a recommender system. I have a list that shows me what a user has disliked and I use it to create a dataset. The dataset shows me: ...
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0answers
45 views

Books/reviews/papers on recommending groups of items?

Looking for books (chapters?)/reviews/papers on the task of recommending a few (possibly non-independent) items. Example: office supply shop recommending a person a pre-compiled package of items of ...
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0answers
738 views

Feeding data to Xgboost for recomender system

I am using xgboost for a recommender system. There are 3-4 recommended content on each page. My data consists of columns like page_id and advertisement_id. Currently for every page_id, there are 3-4 ...
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0answers
202 views

KNN on collaborative filtering

After I calculated the similarities matrix, how do I get the neighbors, for example, consider the matrix of similarities between users, if I did not make any mistakes, the matrix must be symmetric ...
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0answers
583 views

Spark MLlib recommendation - restaurant/ item similarity - issues/improvement

Use Case Recommend similar items (restaurants) to diner. Solution: We have used apache spark MLlib ALS algorithm. Values for lambda and rank has been obtained by iterating through all permutations ...