Questions tagged [recommender-system]
Everything related to recommender systems
419
questions
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13 views
Question: What are Collaborative filtering recommending Systems of X based on Y called?
I have a dataset of users who have X items and Y (different types of) items. The data is implicit so no ratings are involved.
Now, the recommender systems examples I have found online so far recommend ...
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1answer
25 views
Is it bad to use "coefficient of determination" for recommendation?
This is a general question about recommendation:
Is it a bad idea to use "coefficient of determination"($R^2$) as metrics for recommendation?
I am building a model of recommendation and ...
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0answers
7 views
Amazon Personalize Recommendations on Subset of Items
I am playing with AP to build a recommendation system and have a question that I am unable to find answers anywhere.
My interactions dataset and items dataset contain several items. But I want the ...
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0answers
13 views
How can I combine the information from these two dataframes?
If one of my dataframes gives me some info about items:
...
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0answers
8 views
How to generate more market basket association rules for products with smaller basket sizes?
I'm working with data where many customers only buy 1-3 products at a time, meaning that there aren't enough products being purchased together for the market basket algorithm to determine associations....
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0answers
41 views
When should I use neural networks?
I am struggling with this exercise. The objective is "to build a recommendation system that predicts the next video" viewed by a user, given the data provided.
So, the dataset consists in ...
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9 views
How to inference LTR (Learning-to-Rank) models?
I've recently started looking into LTR models such as RankNet and LambdaMart. In the instance of LambdaMart and the LETOR dataset, I believe the model accepts the following as training input: query_id ...
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0answers
39 views
Apriori algorithm with tags
In apriori algorithm, we can create association rules with respect to the frequencies of the corresponding data set. My question is, what if we have tags data in addition to the transaction data. For ...
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8 views
Supply partial inputs to trained model, model fills in missing inputs (for optimal solution)
Summary of issue:
Given a model trained on some input and output data, I'd like to be able to then query the model with a subset of input data, and return a set of missing inputs that would give an ...
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1answer
8 views
Recommendation algo for completing a set
In Gmail, when I start typing out the "to" field, it suggests people to add to the email, based on whom I usually email together. Does anyone know where I can find a simple algorithm of this ...
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13 views
How to predict a disease based on medical history
I have this problem where I need to predict if a patient has a disease based on his medical history. Each observation in the dataset corresponds to one diagnosis of one patient. So, we can have for ...
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0answers
22 views
Transparent Matching / Recommendation System [closed]
I am thinking of a matching/recommendation algorithm which matches students to the right teachers for their individual problems.
The dataset would look like this:
Student
Name
Age
Gender
Weak ...
1
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1answer
48 views
How to choose embedding size for tensorflow recommender system
I am going to build a recommender system using TensorFlow recommender and the two-tower-model. I have wondered, how to choose the size of the embedding dimension. Are there any papers on this for ...
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24 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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0answers
12 views
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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0answers
10 views
Building crop recommender system with past cultivation data not with ratings
I am planning to create a Crop recommendation system for farmers using the past ten years' crop cultivation data. it is a mobile application. whenever a farmer selects his location, the system will ...
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27 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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0answers
20 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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10 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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24 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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2answers
44 views
What methods exist to handle non politically correct recommendations?
Every now and then we hear about another ML-based recommendation system that suggested a politically offensive result to users. What methods are currently in use to prevent such cases in modern ...
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25 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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0answers
17 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 ...
0
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1answer
15 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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0answers
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 ...
0
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1answer
18 views
Any well documented algorithm/function for previously bought recommendation system
I'm working on a previously bought recommendation system for a project. The list I'm trying to sort is static and does not change over time. Assuming each user purchases different items at different ...
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0answers
13 views
Using Position as Feature in offline learn to rank
I have been wondering about a particular technique to denoise position bias in learn-to-rank.I am aware of inverse propensity weighting techniques. During a discussion, it was suggested to me , ...
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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 ...
0
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1answer
22 views
RecSys - Large dataset, few resources, how to sample?
I have been working with a RecSys model, for the first time, by experimenting with matrix factorization and matrix factorization with EmbedNN's. However, I am running into a memory problem since my ...
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0answers
29 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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0answers
52 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 ...
4
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3answers
298 views
Treating recommender systems as multiclass classification or binary classification problem
I'm thinking about the two following approaches for building a recommender system to recommend products using implicit data as a classifier:
Treat it as a multi-class classification problem. The ...
1
vote
1answer
29 views
Reommender system model Predicting the time watched duration for each user_id-video_id pair
I just want to ask If I can use Surprise Library (SVD algorithm) in building a recommender system that predicts the watch duration for a user_id and video_id pair?
I have a dataset that contains the ...
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2answers
212 views
Advantages of matrix factorization when the number of products is low
I'm building a recommender system where the number of products is rather low (around 50), and we can assume it'll stay the same for a long time.
I'm looking at two different way of tackling the ...
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0answers
45 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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0answers
15 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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0answers
34 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 ...
0
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1answer
49 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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0answers
9 views
Searching for movie dataset containing movie synopses? [closed]
To build a hybrid recommendation system, I used the movielens 1M dataset, for the collaborative filtering part. Now, I'm looking for a database/dataset that contains descriptions/summaries/details/...
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0answers
38 views
Dot product of two matrices in NLP how can i get this error be solved [closed]
from sklearn.metrics.pairwise import linear_kernel
sim_matrix = linear_kernel(tfidf_matrix, tfidf_matrix)
when I try to get dot product I am getting this errro
<...
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21 views
Recommendation System with ALS Implicit
I created a model for Recommending top 10 items to users similar to the approach used here https://github.com/benfred/implicit/blob/master/examples/lastfm.py
I wanted to evaluate the model using NDCG ...
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0answers
14 views
is it better to use embedding with attributes in collaborative filtering or content-based approach?
I have a dataset with different text documents, a set of users who each read a different document, some historical info such as their reading speed, and other attributes related to the texts and users....
0
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1answer
36 views
Custom POS tagger for health issues [closed]
I am new to NLP, I have a bunch of raw data that is not tagged at all of medical questions, I need to extract from them what are the health issues stated in those texts.
I was thinking I need to ...
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1answer
42 views
Is it possible to implement a Recommender System without having a ratings/previous purchases similar data?
I'm trying to implement a recommender system for a website that hosts a wide variety of software and you can search the website to find what you need. The need is to implement a recommender system to ...
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0answers
21 views
Recommender System Approaches
I have a 4 datasets with user features, item features, user-item rating and User-item link data. I'm trying to build a recommender system to recommend top 10 items to the user by maximizing NDCG as ...
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0answers
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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0answers
14 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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0answers
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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1answer
35 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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0answers
13 views
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 ...