Questions tagged [recommender-system]

Everything related to recommender systems

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13 views

Recommender System for mostly unique user and items

I am trying to develop a recommender system for a job matching problem. My data consists of past matched candidate profiles and job profiles as well as if there was a success such that both, candidate ...
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1answer
19 views

Evaluate document similarity / content-based recommender system

I'm planning on building a basic content-based recommender system with word2vec and cosine similarity. The data consists of 300k documents in varying length. How do I evaluate my model if I have no ...
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Actual topics for researches in recommender systems [closed]

I'm learning DL and naturally like things such as recommender systems, so I've chosen it to be my theme for bachelor's thesis. I'm reading papers and watching lectures, but i can't hidlight paths in ...
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1answer
20 views

LightFm - replicate precision@k score with predict vs. predict_rank method

LightFm has two methods to predict: predict() and predict_rank(). The evaluation function ...
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25 views

Why softmax in YouTube’s DNN recommender

I am confused about the softmax layer of YouTube’s DNN candidate generation. A user may interact with many videos. Softmax is assuming classes are exclusive. For example, logits = [[4.0, 4.0, 1.0]], ...
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23 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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70 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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11 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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1answer
31 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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1answer
17 views

finding similarity of a new datapoint

I have built a recommendation engine using cosine similarity. When I want to find all the records similar to a given record that is already present in the dataset it works. Consider a case, a user ...
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1answer
18 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

How to represent genre or artist name in a neural network

I am writing a music recommendation system using machine learning. I'm attempting to make sense of ensemble networks to allow the system to learn from both the content-based features, as well as the ...
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1answer
39 views

User-to-item and item-to-user recommendations

I'm currently creating a recommender system and there are different types of the systems. Does anyone know something about the user-to-item and ...
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26 views

How to determine if item-to-item similarity is high (relatively), using cosine similarity

I'm trying to explain part of my recommendations based on item similarity. I have a trained model based on Item-Item cosine similarity that performs well. Given two items, ...
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1answer
21 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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1answer
66 views

Recommender Model for Human Action in Income Protection

Problem Domain I'm working on a project that involves building a model to provide recommendations on the next best step for Human supervisors to take on income protection claims. Income protection is ...
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14 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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19 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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9 views

Item-to-Item similarity: is weighted sum the most popular approach?

In content-based filtering (CBF) recommenders, when there are is no user profile, similar items are recommended an item that a user is currently inspecting. For instance, if you are looking for a ...
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20 views

Recommendation Systems User Profile Streaming Data on GCP

I have a recommendation system that recommends articles to different users. I am planning to provide the recommendations in an off-line fashion. Where I already have a table in BigQuery which has the ...
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1answer
33 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), ...
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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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14 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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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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12 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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9 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 ...
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34 views

Human intuition behind SVD in case of recommendation system

I checked the SVD for recommendation engine thread but it 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 ...
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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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24 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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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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55 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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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 ...
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1answer
55 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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81 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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26 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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1answer
21 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 ...
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17 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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1answer
69 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 ...
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1answer
36 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 ...
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1answer
102 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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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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43 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 ...
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2answers
168 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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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 ...
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1answer
55 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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16 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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44 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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