Questions tagged [recommender-system]

Everything related to recommender systems

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4
votes
1answer
450 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
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2answers
245 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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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 ...
0
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1answer
434 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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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
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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,...
6
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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 ...
1
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0answers
89 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
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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
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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
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0answers
80 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
361 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
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6answers
391 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
67 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
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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
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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
149 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
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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
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0answers
122 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
1k 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
76 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
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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
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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
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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
votes
1answer
34 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
176 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
305 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
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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 ...
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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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
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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. ...
2
votes
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
votes
3answers
1k views

How to use ML to forecast sales of a brand new product

I am working on a forecasting problem and came across this issue. How do I forecast sales of a brand new product? For example, a product has been introduced in the store and the store would like to ...
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
310 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
vote
2answers
198 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 ...
1
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0answers
120 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
votes
0answers
192 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
vote
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
613 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 ...
2
votes
2answers
98 views

Predict the next player's option for betting based on playing history?

I have a project which is to predict in next time, which option player will select for betting. This prediction based on his history. For example, the player have time series data, the last options ...
3
votes
2answers
159 views

Learning to Rank Application

If there's a website/app that sells products and my job is to determine the order/ranking in which the products should be displayed. For example : I click on restaurants and a list of restaurants ...
4
votes
2answers
194 views

Price optimization for tiered and seasonal products

Assuming I can collect the demand of the purchase of a certain product that are of different market tiers. Example: Product A is low end goods. Product B is another low end goods. Product C and D are ...
3
votes
2answers
1k views

Recommendation engine with mahout

I have a list user data: user name, age, sex, address, location etc., and a set of product data: Product name, Cost, description etc. Now I would like to build a recommendation engine that will be ...
0
votes
1answer
347 views

Skills based recommendation system

Assuming that I have a list of Users with a list of skills: (each value is a different skill) And a list of Tasks with a list of demanded skills: Based on a manual classification that returned: (...
1
vote
2answers
2k views

User-based nearest neighbour implementation in R?

I am just starting to learn to use R and am not sure how to find the best packages yet. I am looking for a package that will allow me to calculate user-based nearest neighbours as an input for a ...
1
vote
0answers
16 views

How do I store/model data needed for my recommendation module?

I'm reading data from a store's product catalog, a 100mb xml file which contains product-wise attributes like prices, categories, etc. Given a product_id, my job ...
2
votes
1answer
536 views

How to create user and item profile in an item to item collaborative filtering? (Non-rating case)

I want to build a recommender system for a coupons website which should do the following: Given the past purchase behaviour of a user, recommend coupons which the user is likely to buy. The data does ...

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