Questions tagged [recommender-system]

Everything related to recommender systems

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6
votes
1answer
2k 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: ...
3
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0answers
51 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
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1answer
4k 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
61 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
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1answer
71 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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0answers
81 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 ...
0
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1answer
948 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
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 ...
1
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2answers
58 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
63 views

Student-Teacher matching 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 ...
1
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0answers
79 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
322 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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1answer
36 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
370 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, ...
1
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1answer
50 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 , ...
1
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0answers
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 ...
1
vote
1answer
140 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 ...
2
votes
2answers
87 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 ...
2
votes
1answer
218 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
112 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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3answers
1k 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
69 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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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 ...
1
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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 ...
0
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1answer
32 views

How to validate recommender model in healthcare?

In order to validate a recommender model, a usual approach is create a hold-out set that will provide random suggestions (similar to an A/B testing setup). However, in healthcare applications, this ...
1
vote
1answer
25 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 ...
3
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1answer
174 views

What is the range of values of the expected percentile ranking?

I'm currently reading Hu, Koren, Volinsky: Collaborative Filtering for Implicit Feedback Datasets One thing that confuses me is the "expected percentile ranking", an function the authors define to ...
5
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1answer
459 views

Understanding Youtube recommender (candidate generation step)

I'm trying to understand Deep Neural Networks for YouTube Recommendations. Their candidate generation step outputs top N items via softmax (with negative sampling) at training time . via ...
1
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1answer
98 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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0answers
36 views

Mining Association rules from a data warehouse and a transactional database [closed]

I wonder if it is possible to perform market basket analysis to extract the association rules from a data warehouse and a transactional database in the same time to predict the future purchases of a ...
1
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2answers
52 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 - ...
6
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2answers
1k views

Do recommendation systems necessarily use machine learning algorithms?

I am studying about evaluation of both recommendation systems and machine learning algorithms in recent times, trying to define a scope for my masters research. After some reading time I'm starting to ...
1
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1answer
216 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] ...
1
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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 ...
0
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1answer
61 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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4answers
95 views

How to match a user with another user based on their taste?

Information available Consider that there are N users on a platform. Every user adds items that they like on their profile. These items have static attributes that describe the product. ...
0
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2answers
184 views

How to match a user with other users with similar interests based on their attributes?

Information Available Consider, there are 'n' users and they have these attributes and values ...
1
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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 ...
2
votes
1answer
298 views

How to learn irrelevant words in an information retrieval system?

Right now my recommender system for information retrieval uses word embedding stogether with Tfidfs weights like written here: http://nadbordrozd.github.io/blog/2016/05/20/text-classification-with-...
1
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2answers
179 views

Classification model for recommender system?

I have some data for various customers choosing one of 'n' products or no product. I have some useful features for each customer. I can build a multi-class classification problem out of this data and ...
2
votes
3answers
9k 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 ...
1
vote
1answer
846 views

Does sum of embeddings make sense?

Referring to the LightFM model from paper Metadata Embeddings for User and Item Cold-start Recommendations, the model tries to learn $d$-dimensional user and item feature embeddings $e_f^U$ and $e_f^...
4
votes
1answer
93 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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0answers
116 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 ...
2
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1answer
58 views

How to select random data for two different recommender systems?

The business problem: We have two different vendors that offer personalized recommender engines and want to do A/B testing with them. The recommendation will give the user a personalized offer via a ...
2
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0answers
187 views

Regularization term in Matrix Factorization

I'm trying to build a naive recommender system using latent factor model for MovieLens dataset. From the observed set of ratings I'm trying to build a model which will decompose the sparse matrix to N ...
1
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1answer
30 views

Is this matrix correctly built?

I was reading an article called "Ensemble learning in recommender systems: combining multiple user interactions for ranking personalization" where they explain a method they use called "BPR ...
3
votes
1answer
609 views

Create recommendation system to recommend products to a customer on any e-commerce website

The recommendations should be based on the products consumer has searched on other sites like Google. This basically means, that recommendations have to be made to the user based on his/her search ...
1
vote
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 ...
3
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4answers
4k 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 ...

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