Questions tagged [recommender-system]

Everything related to recommender systems

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3answers
19 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: ...
1
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1answer
9 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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1answer
39 views

Learning similarity of representations

I am interested in a framework for learning the similarity of different input representations based on some common context. I have looked into word2vec, SVD and other recommender systems, which does ...
2
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1answer
33 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. ...
1
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1answer
70 views

Understanding Youtube recommender (candidate generation step)

I'm trying to understand https://storage.googleapis.com/pub-tools-public-publication-data/pdf/45530.pdf Their candidate generation step outputs topn items via softmax (with negative sampling) at ...
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0answers
8 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 ...
1
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1answer
485 views

Calculate similarity on boolean data

I am trying to implement simple recommender system and I am trying to understand different approaches to achieve my goal. My dataset consists of users and items that they bought. I have information ...
0
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1answer
25 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
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0answers
10 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 ...
0
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0answers
12 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 . [
0
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1answer
13 views

learning a distance metric from the output of a knn output

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
47 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
12 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
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1answer
25 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 ...
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1answer
10 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, ...
4
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6answers
158 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
6 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
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2answers
1k views

Mean Average Precision python code

How do you compute MAP in python for evaluating recommender system effectiveness? Is there any library in sklearn or code in python for it? I would like to compute the effectiveness of my Recommender ...
2
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1answer
41 views

Similar students using Machine Learning

I have a student performance data, where I have marks of various subjects for the students and I want to find similar students with good marks in a particular subject using machine learning. How do I ...
1
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1answer
38 views

How to use testing data set to measure recommender system algorithm

I am new to recommender systems and am trying to build one using item-to-time CF. Currently, I am trying to evaluate/measure results using MAE. I have one step which is unclear (after I managed to ...
0
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0answers
15 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 ...
1
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1answer
27 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 , ...
0
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0answers
7 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 ...
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0answers
14 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
7 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, ...
2
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1answer
199 views

Use of negative correlation coefficient in pearson correlation algorithm for recommender systems

I'm new in recommender systems and I try to find similar users of a base users for user-based collaborative filtering. When I calculated the similarity score now between two users (based on there ...
16
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2answers
7k views

Recommending movies with additional features using collaborative filtering

I am trying to build a recommendation system using collaborative filtering. I have the usual [user, movie, rating] information. I would like to incorporate an ...
3
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3answers
730 views

Solution for in Time/Space Complexity challenge in Recommendation System?

I have a book Recommendation System project and have a huge data set of feature vectors. What is the best solution for in memory computation? I mean, the program should: calculate the cosine ...
0
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0answers
18 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 ...
2
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2answers
81 views

Matrix Factorisation Improvement

I am using SGD matrix factorisation (python) using the movielens dataset to make recommendations. I have a website which allows users to give feedback which is positive or negative to whether an item ...
0
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0answers
20 views

Building recommendation engine from transactions data

I am trying to build a recommendation engine for an e-commerce company and I have the following input files : 1) past user transactions + in-app events 2) a new list of campaigns I should recommend ...
0
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1answer
38 views

Null predictions for ALS in Pyspark

I am trying to read from my dataset which has three coloumns. (User, Repository and Number of Stars) In[10] ...
0
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0answers
7 views

How to reduce complexity of inference stage in recommender systems?

Given a large set of customers and a large set of items, how to make predictions given a model like this one: https://arxiv.org/pdf/1606.07792.pdf As stated in the article: "Since there are over a ...
1
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1answer
32 views

Creating a Feature to determine popularity

I am Building a Recommendation System in which i have Multiple Category , I want to Know how Popular is my Product in each Categories. For that I am considering Probabilty as one factor. For e.g I ...
1
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1answer
60 views

Use machine learning to predict next schedule meeting for sales officers

I have a project with data of sales field officers who visit their customers and enter the progress details. Visit can be an order or any kind of customer interaction. Let's say one sales guy has ...
4
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1answer
125 views

Recommender system for next career step

I want to build a recommender system that suggests the next step in your career. About the dataset. About 50'000 Users with following informations: Skills (tags, string value) every job they did (...
-1
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2answers
196 views

Does a matrix factorization recommendation engine use user/item related features?

All the tutorials I can find about matrix factorization recommendation systems start with importing users, items, and user-item-ratings, but then only use the rating matrix to train the recommender (...
0
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0answers
11 views

We know the subspace generated from the data instances, but we cannot constitute the origin space

I was wondering, what if we know the subspace generated F from the data instances, but we cannot constitute the origin space E that can be in higher dimension, and can easily lead us to the true join ...
2
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1answer
33 views

Calculate a ranking function from classification features

I am using 3 features (x1, x2, x3) for binary classification. All my feature values are in 0 to 1 range (unit range). I obtained how important each feature was in ...
0
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1answer
96 views

recommender systems : how to deal with items that change over time?

Let's say I am building a recommender system where items change through time. We suppose that each transaction is composed of : an item $i$ in list of items $(i_1, i_2, i_3, .., i_m)$. a user $u$ in ...
2
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2answers
678 views

Can a recommendation system be built without any user ratings?

I was planning to make an artwork recommendation system as a project by using the WikiArt open source dataset available on kaggle, I'm still looking for datasets which might already have user ratings ...
0
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2answers
122 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 ...
0
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0answers
13 views

What is the accepted level of persona coverage for Recommender Systems?

Almost all of e-commerce companies use recommender systems which involve a set of personas. (explained in this post). "Your personas will never cover 100% of your users" In practice, what is the ...
0
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0answers
21 views

scala spark FP-Growth no results displayed

I have implemented the FP-growth algorithm and it works fine with this sample data: r z h k p z y x w v u t s s x o n r x z y m t s q e z x z y r q t p when I ...
0
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0answers
14 views

I got a overall mean average precision score of 0 for a recommendation engine

I just wanted to know if receiving an overall MAP score of 0 in a recommendation engine was possible, or a sign that my calculation or my logic for the engine was wrong.
2
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1answer
307 views

cosine similarity between items (purchase data) and normalisation

I'm using IndexedRowMatrix which represents the products's user purchase behaviours and in order to build product recommendations, I use cosine similarity to calculate similarities between products. ...
2
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0answers
94 views

Cosine similarity with arrays contaning NaN

I am trying to calculate a cosine similarity using Python in order to find similar users basing on ratings they have given to movies. As it can be expected there are a lot of NaN values. I am using ...
0
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1answer
22 views

How many time a recommender system can recommand the same item to an user?

I'm working on an hybrid music recommender system project, my goal is to create recommendation playlists in accordance with users tastes. I already implemented the first part which use a collaborative ...
1
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1answer
38 views

How to recommend items after finding similar users in recommendation system

As the title explains my problem, I'm done with creating a recommendation system that can give me similar users for any given new user. The problem I face is, If I extract the list of products that ...