Questions tagged [recommender-system]
Everything related to recommender systems
298
questions
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6 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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0answers
7 views
user scores based model for making recommendations
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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0answers
6 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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0answers
39 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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1answer
30 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 ...
0
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1answer
17 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. ...
0
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1answer
15 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 ...
1
vote
1answer
62 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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18 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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0answers
29 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 ...
4
votes
1answer
64 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 ...
0
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1answer
21 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
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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0answers
18 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 ...
0
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0answers
8 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:
...
6
votes
1answer
137 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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0answers
18 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
8 views
Testing Setup in Temporal Tensor Factorization for Recommendation
I am trying to wrap my head around Temporal Tensor Factorization for Collaborative Filtering, as described in the paper: Temporal Collaborative Filtering with Bayesian Probabilistic Tensor
...
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1answer
37 views
Understanding the “Wide” part of Google's wide and deep
Google's wide and deep recommender model sounds really cool, but I'm struggling to believe I'm grasping the wide section right so wanted to check my understanding.
Their paper says the following:
...
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0answers
13 views
Can we treat sentiment score of the review text as rating of the product?
I have a review text of the different products, And I need the rating of the product. So can we use sentiment score as the rating of the product.
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22 views
Recommendation system without user data
I have a recommendation project to build without user data.
Suppose I am building a initial recommendation system with the initial dataset with me only consisting of
...
0
votes
1answer
29 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 ...
1
vote
2answers
69 views
Recommendation system depend on user rating and favorite list
In my project I have a database of Japanese Sake(rice wine).Each Sake has following attributes which has direct link to the taste of the Sake:
classification (enumeration 1-5 integer)
alcohol ...
0
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0answers
11 views
SVD++ in matrix form
I have been recently reading the following presentation and papers preceding it:
http://staff.ustc.edu.cn/~ynyang/group-meeting/2014/matrix-factorization/Matrix-factorization-recommendation-system-...
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0answers
29 views
Mobile App Recommendation: How to get the rate of a specific user submit for a specific application
I have a mobile app recommendation project, so I need data set which has user-app matrix-rate.
Actually, I want to know what rate does a specific user submit for a specific application.
in other words,...
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0answers
12 views
In learning latent factors in matrix factorization, are weights learned based on similarity between e.g. users?
I implemented a recommendation system using user-user interaction data, learning missing ratings through alternating least squares and matrix factorization, which as I understand it, adjusts and ...
5
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1answer
171 views
How is the cross-product transformation defined for binary features?
I am reading the paper on Wide & Deep learning and for the wide component, it states that one of the most important transformations is the cross-product transformation. This is defined as follows:
...
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0answers
14 views
supervised similarity scoring system - recommender system
I have a dataset of movie collections with 10-15 features describing each movie. I also have a dataset of user ratings of the similarity between some random pairs of movies.
Using both of these data ...
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0answers
27 views
What is the difference between row-wise and column-wise Z-score normalization?
I have a data set, each row represents a movie name, each column is a feature (such as genres), I want to perform cosine similarity to find out the similarity between each movie, before that I need to ...
3
votes
0answers
40 views
What is the “matrix trick” in recommendation systems?
I just found slides from Matt Gormley (CMU) about recommendation systems. Under the heading "Unconstrained Matrix Factorization" he mentions:
Optimization problem
SGD
SGD with Regularization
...
2
votes
1answer
502 views
memory error in matrix cosine_similarity
I have (20905040, 7)
of a dataset to recommend 10 different product to the user
it could be larger than that but anyway I got memory error when processing the
...
0
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3answers
36 views
If I have to recommend 10 movies to the users
Let's say I have some information about a user and movie data similar to the following:
...
2
votes
1answer
40 views
Item-based recommender using K-NN
I'm trying to build an item-based recommender using k-nn. I have a list of items, all of which have some properties (features) in common.
...
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0answers
25 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
5 views
How to validate model which outputs movies that are similar with no training data
At a high level, my code takes a wide variety of movie related features and computes a large cosine similarity matrix and assesses which movies are most similar.
I don't have any validation data so ...
0
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1answer
151 views
Predict Customer Next Purchase with Sequence
Suppose I buy products: [1,2,3,4]
Another customer X bought: [2,3]
Most probably customer X next purchase will be: 4
Sequence is very important in my problem
I tried association analysis using R, ...
1
vote
0answers
20 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
49 views
what will be the best algorithm for find similar users based on user features , betwenn knn, euclidian or jaccard?
I have user data table containing user data like university, gender, city, id etc. I also have a matrix data-set like this .
[
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2answers
37 views
Reverse engineering a distance metric from the output of a k-NN
Suppose that someone has trained a nearest-neighbor algorithm based on some unknown metric. I have a large dataset of $N$ observations and $P$ features. For each observation, I am given $K$ indices ...
0
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1answer
57 views
Student-Teacher maching problem
The problem I want to solve is as follows:
I have data about how many teaching hours different students spend with their teacher in order to pass their exams. The teaching varies from 25-55 hours. In ...
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0answers
33 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?
2
votes
1answer
40 views
How does recommendation by matrix factorization deal with new movies / users for which there are ratings?
Assume you have the ratings of $n$ users for $m$ movies in a matrix $R \in \mathbb{R}^{n \times m}$. You compute a representation
$$R = U \times \Sigma \times V$$
by initializing $u_i, v_j \forall i ...
0
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0answers
7 views
Recommender with global explicit feedback
I've to build a recommendation system with a dataset where the feedback is given for the whole set of items instead to the specific items. We can see that feedback as a numerical indicator of the ...
0
votes
1answer
14 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, ...
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0answers
19 views
Handling collection of featurevectors for classification
I have a data set where devices are represented by a collection of variables. These variables consist of several properties like a name, datatype, driver, limit values, etc. (mixed data; quantitative ...
4
votes
6answers
182 views
Distance between users
I want to compute the "distance" between users in order to return the top n similar users, for any given user.
For each user a have a bunch of features.
This is close to a recommendation system, ...
0
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0answers
8 views
Building a dynamic recommender system that changes based on how users rate
I am trying to build a recommender system for coding interview questions.
I thought of doing a collaborative-filtering, but it is hard to get data on how other users rated the questions.
I currently ...
1
vote
1answer
31 views
Recommender systems and Machine Learning
According to Mitchell:
“A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T , as measured by P , ...
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0answers
25 views
Building a personalized recommender system for coding interview questions?
I am trying to build a recommender system for coding interview questions.
Let's say I have data for interview questions and the features are
...
0
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0answers
12 views
Any library recommendations for a Python recommender framework with multi-class input, incl. array input?
(crosspost from https://softwarerecs.stackexchange.com/questions/62491/python-recommender-framework-with-array-input, this meta post seems to justify doing this. I really really need answers to this, ...
