Questions tagged [recommender-system]

Everything related to recommender systems

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Question: What are Collaborative filtering recommending Systems of X based on Y called?

I have a dataset of users who have X items and Y (different types of) items. The data is implicit so no ratings are involved. Now, the recommender systems examples I have found online so far recommend ...
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57 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 - ...
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3answers
99 views

How to recommend items after finding similar users in recommendation system [closed]

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 ...
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1answer
454 views

Can a recommendation system be used as a binary classifier?

I have a computer-generated music project, and I'd like to classify short passages of music as "good" or "bad" via machine learning. I won't have a large training set. I'll start by generating 500 ...
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1answer
25 views

Is it bad to use "coefficient of determination" for recommendation?

This is a general question about recommendation: Is it a bad idea to use "coefficient of determination"($R^2$) as metrics for recommendation? I am building a model of recommendation and ...
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2answers
450 views

Neural network model for sparse multi-class classifier on Tensorflow

The problem I'm trying to solve is the following: the data is Movielens with N_users=6041 and N_movies=3953, ~1 million ratings. For each user, a vector of size N_movies is defined, and the values ...
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1answer
137 views

How to estimate missing values when calculating NDCG

I would like to compare recommendations methods using NDCG metric on MovieLens dataset. In ranking problem, the goal is to rank items based on their relevance for user. Ranking models can be learned ...
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333 views

Which metrics for evaluating a recommender system with implicit data?

I am currently in the process of creating a recommender system. This recommender system works with a neural network and then searches for the closest neighbors and thus gives recommendations for a ...
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1answer
109 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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1answer
82 views

Initialize a recommender system with no dataset

Consider a platform for content recommendation based on the user history. The contents are books and articles and by history I mean what the user has read, what he has shared and so on. I know that ...
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8 views

Amazon Personalize Recommendations on Subset of Items

I am playing with AP to build a recommendation system and have a question that I am unable to find answers anywhere. My interactions dataset and items dataset contain several items. But I want the ...
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1answer
117 views

How do I build a recommend system based on user's past purchases?

I am exploring approaches to build a model that shows personalized search results (with or without query) for a fashion eCommerce platform. For that I am first working on coming up with a bunch of ...
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319 views
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65 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 ...
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114 views

Neural Network - Sparsity of collaborative based filtering and modelling the prediction problem

I'm fairly new to machine learning and for that matter, neural networks, but for the past couple of days I decided to take a stab at a fairly classical and practical problem of neural networks/machine ...
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1answer
78 views

Recommender system that connect users with each other , should I go for content based or collaborative filtering?

I am trying to build a system where user come on the platform and he chooses a topic(predefined few topics) and then we connect him with any random online user who chooses the same topic. Then they ...
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77 views

Best approach for A/B testing two different recommendation systems

I have two recommendation systems for musical preference that make a list of predictions for a particular user based on the songs they have saved in their library. The user then rates how good each ...
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1answer
76 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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1answer
294 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 ...
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419 views

Proper evaluation method for recommendation system with implicit feedback?

I am trying to implement a recommendation system for a live-streaming website. Here "users" are simply the website users and "items" are streamers that they should watch. I ...
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170 views

Click Through Rate calculation (CTR) calculation problem

So I'm doing a use case for a company interview and one of the questions is to calculate the CTR for a sorting algorithm. My question would be: Should I remove the operations where there were no ...
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1answer
997 views

how to build word2vec content based recommendation?

I am building a content-based recommendation system for hotel accommodation. I have a hotel name, hotel description and location. I combined hotel name, description and location. Then, applied NLP and ...
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8 views

How to generate more market basket association rules for products with smaller basket sizes?

I'm working with data where many customers only buy 1-3 products at a time, meaning that there aren't enough products being purchased together for the market basket algorithm to determine associations....
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1answer
385 views

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

I am new to recommender systems and am trying to find similar users of base users for user-based collaborative filtering. When I calculated the similarity score between two users (based on their ...
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41 views

When should I use neural networks?

I am struggling with this exercise. The objective is "to build a recommendation system that predicts the next video" viewed by a user, given the data provided. So, the dataset consists in ...
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1answer
58 views

Recommendations based on other products seen

I am trying to develop a basic book recommender system to get in touch with the field and start learning methods and how to prepare the data. The Dataframe I am using is pretty plain, it has the ...
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1answer
29 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 <...
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97 views

Can we use embeddings or latent vectors for a recommender system?

I'm having a hard time understanding why people use any vector they find as a candidate for a recommender system. In my mind, a recommender system requires a space where distance represents similarity....
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49 views

Change feature importance in a trained model

I am giving a toy example for describing a real world business problem. Let's say I am a publisher and I have some book stores to visit. By visiting those stores I will check whether they have ...
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How to inference LTR (Learning-to-Rank) models?

I've recently started looking into LTR models such as RankNet and LambdaMart. In the instance of LambdaMart and the LETOR dataset, I believe the model accepts the following as training input: query_id ...
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1answer
52 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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40 views

Apriori algorithm with tags

In apriori algorithm, we can create association rules with respect to the frequencies of the corresponding data set. My question is, what if we have tags data in addition to the transaction data. For ...
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8 views

Supply partial inputs to trained model, model fills in missing inputs (for optimal solution)

Summary of issue: Given a model trained on some input and output data, I'd like to be able to then query the model with a subset of input data, and return a set of missing inputs that would give an ...
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1answer
118 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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1answer
8 views

Recommendation algo for completing a set

In Gmail, when I start typing out the "to" field, it suggests people to add to the email, based on whom I usually email together. Does anyone know where I can find a simple algorithm of this ...
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591 views

What's the best classification model for this recommendation engine?

I am not a data scientist but am trying to implement a recommender system for my company. My application runs on PHP but I will use Python to process the data. My company is an online school, with 40 ...
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1answer
61 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 ...
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14 views

How to predict a disease based on medical history

I have this problem where I need to predict if a patient has a disease based on his medical history. Each observation in the dataset corresponds to one diagnosis of one patient. So, we can have for ...
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2answers
851 views

What is difference between Nearest Neighbor and KNN?

I was taking the tutorial of making Recommendation system , there I read that Nearest Neighbor is different from KNN classifier . Could anyone explain that what is Nearest Neighbor and how it is ...
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Transparent Matching / Recommendation System [closed]

I am thinking of a matching/recommendation algorithm which matches students to the right teachers for their individual problems. The dataset would look like this: Student Name Age Gender Weak ...
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1answer
294 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 ...
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1answer
48 views

How to model a supervised recommender system with varying data

Suppose there are 2000 movies and a company wants to recommend some movies (for example, at most 5 movies) to each visitor. The objective is to learn how to predict which movie will be selected if a ...
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73 views

How to identify text similarity based on training data?

I have a set of documents (1 to 11) for which the labeling is done. Lets Assume: ...
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21 views

Mutiple binary classification for for best propensity to buy one of the product

Problem:- I have 5 products for sell and I can pitch only one product in a month to one customer.so I wants to know which product customer can buy. Proposed solution:- I build 5 binary logistic models ...
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53 views

Recommendation Engine - Content based and Collaborative recommendation?

I am building a recommendation system for hotel accommodation. I scraped data from online booking portal and now my data has Name of the hotel, review, description and location. I built a simple ...
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1answer
29 views

Reommender system model Predicting the time watched duration for each user_id-video_id pair

I just want to ask If I can use Surprise Library (SVD algorithm) in building a recommender system that predicts the watch duration for a user_id and video_id pair? I have a dataset that contains the ...
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1answer
103 views

Selecting the number of hashes for minhash? Working with extremely sparse data and want more collisions

I'm attempting to use minhash to generate clusters and similarities, and I am primarily using ideas from these resources. http://www2007.org/papers/paper570.pdf https://chrisjmccormick.wordpress.com/...
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33 views

Recommender system: Give a feature more significance than another

I am trying to build a recommender system that predicts hotel prices based on a great number of features. I have a column representing the hotel rating out of 5 and another column indicating the ...
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1answer
51 views

Calculate Similarity using User's Personal Data?

I want to find out which users are similar to each other using their personal/organisational data, such as department, company, site, etc. I have this data in a boolean format, as shown below: ...

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