Questions tagged [recommender-system]

Everything related to recommender systems

Filter by
Sorted by
Tagged with
2
votes
2answers
179 views

How to calculate precision at K and NDCG for ranking algorithms

I am ranking a filtered item list as per user's metadata and historical behaviour. Now how to calculate metrices like precision at K? One approach could be - Divide historical data in training and ...
1
vote
2answers
53 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 ...
2
votes
1answer
27 views

Recommender system that matches similar customers with similar highly rated products?

I have a dataset of 1,000 customers that bought 20 distinct phones and rated them 1-5. I have several demographic attributes for these customers (gender, age). My website offers 100 distinct devices, ...
2
votes
0answers
26 views

Operations on Recommendation Embeddings

I've trained a recommendation system to recommend steam games based on game tags. An example output is shown below, where GAME is the game recommended based on the <...
4
votes
1answer
2k views

How to choose negative examples for recommendation system?

I am building a search recommendation system for e-commerce which generates most relevant results given an input query. I have framed it as a classification problem (learning to rank) and using ...
2
votes
2answers
94 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
votes
1answer
50 views

CV(Curriculum vitae) Recommendation System guidance

I am building a recommender system which matches people's CV with a vacancy. So far, I used TF-IDF & Cosine Similarity to get a matching score between a vacancy and a candidate's CV. I want to ...
2
votes
1answer
415 views

Calculating Rank Ordering Error Metric for implicit recommendation

I'm reading Collaborative Filtering for Implicit Feedback Datasets. On page 6 they detail their evaluation strategy, which they define as mean Expected Percentile Ranking with the following formula: $...
5
votes
1answer
86 views

Evaluating the performance of a machine learned recommendation system

I have a set of resumes $R=\{{r_1,...,r_n\}}$, which I've transformed to a vector space using TF-IDF. Each resume has a label, which is the name of their current employer. Each of these labels comes ...
1
vote
1answer
59 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, ...
2
votes
1answer
374 views

Vectorizing equation in MATLAB

I am working on collaborative filtering using matrix factorization in MATLAB. I am using Gradient Descent for parameter learning. The cost function to optimize is : $ J = {\left\| I \odot (R - U V') \...
1
vote
2answers
60 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 ...
6
votes
1answer
561 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 ...
0
votes
1answer
82 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. ...
1
vote
1answer
2k 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.
1
vote
0answers
50 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 and ...
1
vote
2answers
110 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 ...
4
votes
1answer
487 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 ...
4
votes
2answers
261 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
vote
0answers
29 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 ...
1
vote
1answer
525 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: ...
0
votes
3answers
66 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
vote
0answers
35 views

Mobile App Recommendation: How to get the rate of a specific user submit for a specific application [closed]

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,...
8
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
votes
0answers
53 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 ...
1
vote
0answers
101 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 ...
2
votes
1answer
1k 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
votes
1answer
1k 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
83 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
418 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 ...
4
votes
6answers
447 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
vote
1answer
81 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 , ...
3
votes
3answers
1k 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 ...
1
vote
0answers
47 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
159 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 ...
0
votes
2answers
1k 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
votes
0answers
131 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
votes
1answer
2k 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. ...
0
votes
1answer
78 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 ...
2
votes
2answers
2k views

ROC-AUC loss for GRU Model: Cannot use tflearn's loss in keras

I am trying to use tflearn.objectives.roc_auc_score as a loss function for a GRU network in Keras but I get the following error: ...
7
votes
2answers
6k views

Recommender system based on purchase history, not ratings

I'm exploring options for recommender systems optimized for the insurance industry, which would take into account i) product holdings ii) user characteristics (segment, age, affluence, etc.). I ...
1
vote
0answers
22 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
vote
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
votes
1answer
37 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 ...
3
votes
1answer
186 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 ...
1
vote
1answer
307 views

Which algorithm should be used for an accurate job recommendation system

I'm building a testing project to get an introduction to DS & ML. As a person part of the working force, sometimes finding a job is harder than it should be. I thought I could built a testing ...
1
vote
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 ...
6
votes
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
vote
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 ...
2
votes
4answers
99 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. ...

1
3 4
5
6 7
9