Questions tagged [recommender-system]

Everything related to recommender systems

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26 views

What is the right approach to bucket users for algorithms with different coverage for A/B testing

I've couple of recommendation algorithms that I want to A/B test. Algorithm A has 90% user coverage and algorithm B has 95% user coverage. That means if the algorithms are asked to provide ...
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1answer
22 views

Recommend System AB test metric events

I build personal recomendation system for choosing games. In website on main page on special place there is collection of personal games recomendation. And after AB test(between 2 recommend system) I ...
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81 views

LightFM implementation for scala/java on spark

I am looking for hybrid recommendation libraries such as lightfm that I can use on Spark (with Scala). Any alternative? Or best would be for me to build a hybrid recommendation system on spark's mllib ...
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0answers
37 views

Time aware recommender system

I plan to design a recommendation system, especially with Scikit-Surprise. A bit of background: I want to recommend products to shop for. Here, the user is the shop and the items are products (water,...
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1answer
62 views

How to develop Top-N recommendation for evaluating my system

I want to evaluate my recommender system with the Top-N recommendation method and I have a problem. In some situations, e.g. N = 5, I don't have 5 items for listing and I cannot do that for evaluating....
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1answer
1k views

Is there an overview over recommender system architectures?

I want to learn more about the recommender system topic. I am very interested in the usage of different database systems for this use case. My problem is that I cannot find a good overview of ...
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1answer
37 views

Item-to-Item recommendation using DNN

I am new to DNN still learning, have a need to build item-to-item content based recommendation using DNN. For example, say I have a column of strings where each row represents a document I need to ...
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0answers
78 views

Cross validation for Collaborative filter-based recommendation systems

I am an absolute beginner and am trying to implement collaborative filter for furniture ecommerce (think wayfair). I need some guidance about cross-validation strategy. Situation: I am working on a ...
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0answers
32 views

How does an autoencoder 'fill in the blanks' in the context of a recommender system?

My understanding is that an autoencoder takes an input, produces a lower dimensional representation of the input, which should explain the original features in the dataset, and then reconstructs the ...
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1answer
96 views

Temporal train test split for recommender systems

When evaluating a collaborative filtering recommender system, it is practical to split the data temporally. However, by doing so, some users might be present in only either of the train or test set. ...
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2answers
8k 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 ...
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0answers
14 views

Neural Recommendation System - Explanation

Hello I am working on a recommendation problem in which I want to recommend the next best product to a customer. I am using a collaborative filtering approach but I would like to have as a result, the ...
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1answer
25 views

Reduce serving time complexity for real-time recommender systems

I am working on a real-time recommender system predicting a product to a user using deep learning techniques (like wide & deep learning, deep & cross-network etc). Product catalogue can be ...
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29 views

How to use sklearn's Matrix factorization to predict new users' scores

I'm trying to use sklearn.decomposition.NMF to a matrix R that contains data on how users rated items to predict user ratings ...
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2answers
84 views

New to Data Science - What to use when looking for a pattern/relationship between items and an outcome

I am new to data science and I am hoping I can start applying it to my job. I have watched some videos on places like Udemy for Machine Learning and Python etc. Anyway, I have a task but I am not ...
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51 views

Weighting of features in Recommender Systems

I'm new to Recommender Systems, and wanted to figure some things out in order to make the best possible Content Ranking System. I want to make a ranking of all the content (and content providers) ...
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0answers
34 views

ML recommendation system with items organized in a tree

I would like to develop a recommendation system (probably hybrid, user-based and feature-based) for items which are organized in a tree (there are categories, divided in sub-categories, divided in sub-...
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1answer
32 views

How to find coherence between a large number of sentences

I have a list of sentences returned as a result of a document search algorithm. I want to determine if the results returned are semantically close/similar/coherent using some sort of metric. For a ...
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0answers
15 views

What are the business metrics I should track to evaluate a recommender model deployed on an e-commerce website? [closed]

Can you suggest some google analytics metrics such as (click or impressions etc) to evaluate a recommender model deployed on an e-commerce website.
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23 views

Can latent factor model work for new users?

I am studying latent factor model for recommendor system. It does matrix factorization(like SVD) on the user-item rating matrix. What I am not sure is, does a trained model work for a new user that is ...
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0answers
25 views

(Graph Convolutional Network (GCN) based recommender system maintenance issue [closed]

I have built an item-item recommender model using (Graph Convolutional Network (GCN) for an E-commerce website. Could you please help me with the maintenance of the model. How often should I retrain ...
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14 views

estimate user's satisfaction of a video based on how much of it they watched - normalization

I am trying to estimate how much a user liked a video using how much of the video they watched. Let's say, on the scale of 1 to 10, 1 means that the user didn't like it at all, and 10 means they ...
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0answers
7 views

How is SVD from scikit-surprise handles empty values

I am studying the surprise lib for recommender system. SVD from this lib doesn't require all value input in user-item matrix. But it is a must of the original SVD method. The official doc doesn't ...
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11 views

Top n products as a kind of recommendation system

I'm looking for a paper, book or something similar that describes only the top products as a kind of recommendation in a recommender system. The top products can be determined with a simple counter. ...
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14 views

Why I need to generate train instances and load negative samples?

If you look at this GitHub link ( here is the paper link for the implementation ) you can see that the get_train_instances method generates trainingns instances. In ...
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3answers
473 views

Why is deep learning used in recommender systems?

I am currently reading a lot about recommender systems (RS) and came across that many RS are based on deep learning. However, I never find a good scientific article why deep learning is used in RS and ...
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1answer
26 views

Recommender/Clustering data to support a hypothesis. Is this a valid use-case for unsupervised ML?

I have a dataset where some items have been labelled (categorized into 4 classes [A,B,C,D]). However, there is a vast majority of the dataset which has not been labelled. My hypothesis is that there ...
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4answers
14k views

Can I use cosine similarity as a distance metric in a KNN algorithm

Most discussions of KNN mention Euclidean,Manhattan and Hamming distances, but they dont mention cosine similarity metric. Is there a reason for this?
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2answers
112 views

What is the best model for a recommendation system using implicit ratings?

I have a similariy matrix that looks like this: I have a bunch of user vectors with 1s and 0s, with a 1 indicating that someone has clicked on an email (as part of a campaign) and zero to indicate ...
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1answer
34 views

How to grade an interaction that a user had with a post with an AI based on big data?

Context I'm creating a social network. The thing is, I don't want to order posts by likes, or something like that, I'm using an AI (lightfm in ...
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1answer
32 views

Finding and ranking best semantic matches between two sets of phrases

I'm looking for a proper definition for what sort of problem this is, so I can further research it on my own - though I will, for sure, appreciate any specific advice on what are industry standard ...
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1answer
33 views

Evaluation of recommendation systems

I have developed a content-based recommendation system and it is working fine. The input is a set of documents={d1,d2,d3,...,dn} and the output will be Top N similar documents for a given document ...
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0answers
10 views

Predict the target audience for a new brand using data from other brands and customers buying behavior

Assume a company has a large database about wine, including brand, the taste of the wine, year, place of production, etc, and data of customers' purchase behavior. Now if there is a new brand coming ...
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1answer
96 views

How can collaborative filtering be extended to include more features?

Looking at the following: https://realpython.com/build-recommendation-engine-collaborative-filtering/#using-python-to-build-recommenders I can see that userID, itemID, rating are the standard features ...
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2answers
88 views

Evaluate document similarity / content-based recommender system

I'm planning on building a basic content-based recommender system with word2vec and cosine similarity. The data consists of 300k documents in varying length. How do I evaluate my model if I have no ...
4
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1answer
63 views

Why softmax in YouTube’s DNN recommender

I am confused about the softmax layer of YouTube’s DNN candidate generation. A user may interact with many videos. Softmax is assuming classes are exclusive. For example, logits = [[4.0, 4.0, 1.0]], ...
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1answer
41 views

Recommender System for mostly unique user and items

I am trying to develop a recommender system for a job matching problem. My data consists of past matched candidate profiles and job profiles as well as if there was a success such that both, candidate ...
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1answer
155 views

LightFm - replicate precision@k score with predict vs. predict_rank method

LightFm has two methods to predict: predict() and predict_rank(). The evaluation function ...
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0answers
100 views

Multidimensional collaborative filtering model

I have a dataset that is approximately structured in the following way: 500 users, 500 products, 100 countries, 2 seasons, 300,000 ratings. Meaning that I have 300,000 rows containing unique ...
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2answers
3k views

Train-Test split for a recommender system

In all implementations of recommender systems I've seen so far, the train-test split is performed in this manner: ...
2
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1answer
313 views

How do I predict a set of frequently bought items?

I have a dataset of retail transactions wherein different users buy certain items together. For example, a user A buys a toothpaste, a toothbrush and a floss at the same time, and a user B buys a ...
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1answer
38 views

Recommendation system with active learning

I have data where companies ask users to score a bunch of questions but some items may be randomly chosen while others are personalized. Users score higher in personalized questions on average. I have ...
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0answers
12 views

Adding additional information in content-based recommendations

I have a book dataset where 100 users have rated the books as like/dislike. Each observation with features Table1 : ['user_id','book_name', 'book_genre','author','date_published','like/dislike'] These ...
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1answer
31 views

finding similarity of a new datapoint

I have built a recommendation engine using cosine similarity. When I want to find all the records similar to a given record that is already present in the dataset it works. Consider a case, a user ...
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1answer
31 views

How to represent genre or artist name in a neural network

I am writing a music recommendation system using machine learning. I'm attempting to make sense of ensemble networks to allow the system to learn from both the content-based features, as well as the ...
4
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1answer
41 views

User-to-item and item-to-user recommendations

I'm currently creating a recommender system and there are different types of the systems. Does anyone know something about the user-to-item and ...
3
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1answer
69 views

Recommender Model for Human Action in Income Protection

Problem Domain I'm working on a project that involves building a model to provide recommendations on the next best step for Human supervisors to take on income protection claims. Income protection is ...
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2answers
706 views

Offline evaluation of recommender systems

Let's say I want to compare whether one recommender system (A) is better than the other (B). One approach is to let people rate recommendations returned by both systems. However, there situations ...
4
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1answer
94 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 ...
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0answers
28 views

Learning to Rank vs Reinforcement Learning in Information Retrieval - which one is preferable and why?

I am trying to create an information retrieval system which can benefit from user feedback (either implicit, through e.g., click-through data) or explicit (e.g., binary feedback on irrelevant ...

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