Questions tagged [recommender-system]

A recommendation engine tries to predict how much a user will enjoy certain goods (movies, books, songs, etc) and makes recommendations. They are often used by online vendors to suggest new purchases.

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23 views

Is it useful to add a proportion hyperparameter in the concatenation layer?

I'm reading a paper on deep learning-based recommender systems: Neural Collaborative Filtering. There are two sub-networks, GMF and MLP, which are fused into a unified model, by a concatenation layer. ...
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26 views

Algorithmic recommendations for adaptive content suggestion

I am interested in learning the ins and outs of adaptive content suggestion (similar to what facebook, google ads, youtube, netflix, linkedin and similar services typically do). I am new to the topic ...
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41 views

Clustering/Similarity between drivers

I have a dataset that contains initial and ending points of car trips: ...
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97 views

Factorized matrix for recommendations, what then?

I have a dataset that looks like this: Image taken from this blog Let's assume that I have applied Matrix factorization and have learned the zero values for the items missing for every user. I now ...
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47 views

Learning similarity of representations

I am interested in a framework for mapping together input representations based on some common context. I have looked into word2vec, which does more or less what I want, but I want to know if anyone ...
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167 views

Data normalization for recommender system

Does anyone know whether it's a good idea to standardize your data by replacing it with the percentile which it occupies in a distribution? Instead of substracting the mean and dividing by standard ...
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59 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 ...
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20 views

Build customer ratings from subscription datetime data for a recommendation system

I want to build a recommendation system with only some customer's subscription and unsubscription date. I have a database that looks like: ...
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29 views

Recommender using classification

Hi I'm tasked with building a recommender for predicting item categories to users. I have data about which items the user has viewed and bought respectively. I'm interested in turning this into a ...
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225 views

Why RMSE over MAE for matrix factorisation? [duplicate]

I have been trying to compare several matrix factorization algorithms and I've noticed that all the papers and libraries I've seen measure the Root Mean Square Error(RMSE) when intuitively I would ...
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169 views

Customer similarity for customer-product interactions over time

I have a table that has 3 columns: Customer, Item and Date of Interaction between customer and item. I would like to calculate a similarity between customers based on how these customers interact with ...
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2k views

How to find nearest neighbors using cosine similarity for all items from a large embeddings matrix?

I have an embeddings matrix of a large no:of items - of around 100k, with each embedding vector length of 100. So a matrix of size 100k x 100; From this, I am trying to get the nearest neighbors for ...
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245 views

Getting the confidence interval for Click through Rates

I am trying to analyse the performance of two algorithms , bascially through click through rate and i have arrived at the following form ...
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1answer
150 views

Is brute force conditional probability a good algorithm product recommendations?

I'm creating a recommendations system for an e-commerce web application. I need an algorithm. I've come across conditional probability, which might be what I need. I heard very little about ...
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173 views

Android Recommendation App Algorithm

I have this project proposal entitled "Android Based Program Recommendation App". (This application is for those college students who wants to shift to other programs). The app will find a program ...
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59 views

Machine Learning algorithm for a lack of domain data?

When a user searches for an item to purchase on a retail website they can input some features of their desired item to narrow down their search results. This produces a list of items that match their ...
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117 views

Why low results with Content-Based recommendation?

I'm unable to get a good result with my Content-Based recommendation (very low Precision) Items are different sort of services (Yelp DataSet). To compute the item's profiles, I used a classical ...
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95 views

How do we construct features to use as input to machine learning algorithms for the purpose of movie recommendations(using collaborative filtering)?

I am working on movielens 100K dataset. The idea is to use ML algorithms such as neural nets,SVMs,K-means etc for classification of movies as being rated 1,2,3,4,5. The problem I am facing is to ...
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40 views

What algorithm would be appropriate to find nearest neighbors based on transaction history

I have two data sets with transaction history of customers by date and product (de-identified). These are from two different sources and have different capture rate (e.g.: One might have 5 ...
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58 views

Find the best matching element from a bunch of questions [closed]

First, I am sorry I have poor knowledge of math and statistics (but willing to learn). So it could contain non-sense and I would be glad to precise my thought. Here is the thing; I will have elements ...
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37 views

Building a Diagnostic System for Psychiatric Disorders

I am an undergraduate with near-infinite passion to the theoretical machine learning and ML applications. Inspired from my challenging mental disorders, I am really interested in building a ...
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338 views

Using cosine similarity to measure similarity between uses is not correct

I have a theoretical question. I have implemented a recommender system using collaborative filtering method. There, I am using cosine similarity method to calculate similarity between two users. I ...
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613 views

Spark ALS Recommendation engine with prior clustering

I'm trying to develop a recommendation engine, but since the dataset is too big, I'm trying to divide users in clusters and run the ALS recommender on each single cluster. To do this, I'm trying to ...
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2answers
730 views

Probability of a product being bought given a seed product (recommender system)

I'm building an e-commerce recommender system. Given a seed (bought) product I want to recommend a product that has the highest probability of being bought. I model this as a conditional probability ...
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117 views

How to recommend items based on historical shopping basket contents

Say you know the contents of shopping baskets many clients had at checkout. Based on this, you want to recommend an item to buy based on the item currently in the basket. How would you do this? ...
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934 views

Neural Networks for Content Based Recommendation system

I'm working on the TED Dataset which has the transcript of each TED Talk. I have around 1000 such TED talk transcripts and I need to recommend 3 TED Talks based on the Transcript of these talks. As ...
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121 views

EdgeRank for eCommerce product feed

I am running my eCommerce store with around 1000 products with 10 categories. I want to show these products in feeds. But there are lots of products so its very complex to define priority list for ...
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647 views

Non-negative matrix factorization in recommender systems

As I understand, in NMF we should have our three matrices elements non-negative. But I can't understand how to do it so far. Shouldn't we just initialize our factor matrices at the start with random ...
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43 views

Target definition by recommender

I want to use the Ranking factorization recommender from Graphlab. My question is, what is the exactly difference, when I use or don't use the target parameter in ...
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282 views

Is precision in recommender system related to mean average error (MAE)?

A recommender system is being evaluated while increasing the neighborhood size. The highest precision was achieved between 10-15 neighbors(users) while the lowest MAE was in the range from 30-40 users....
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91 views

Obtain Precision and Recall from Click through data

I am trying to build a graph of precision and recall using click data. I have two data sources. First data source has all the user clicked item_ids based on a given query_id. Second data source has ...
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757 views

Incremental SVD Recommendation System

I have the following Octave/Matlab code to compute an SVD-like matrix-decomposition: ...
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230 views

(binary) Matrix completion with less known data

Recently, I meet such problems, I call it matrix completion problem. For example, the row denotes the users and the column denotes items. And If one user like the ...
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28 views

Adding new item to recommender's options? [duplicate]

My shop has 20-items with a recommender system on top which analyses history of purchases and recommends items to buy each time customer returns. Now I want to add an additional item to choose from, ...
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100 views

Cosine Distance and Recommender Systems

Suppose that a computer is rated according to three numerical features: processor speed, disk size, main-memory size. Consider three computers $A,B$ and $C$ with values: $$A(3.06,500,6)$$ $$B(2.68, ...
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86 views

Calculating user preferences based on purchases: how to incorporate different variables for comparison

I am trying to come up with a metric to calculate user preference correlation for my final project (a web-shop for shoes) at school. Originally I intended to include user ratings and use Pearson's ...
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257 views

How to calculate overall rating from multiple implicit feedback

I have data representing individual feedback ('like'/'not liked', represented in my data as 1/0 repesectively). I also have ancillary data on the length of time individuals have watched courses ('Time'...
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15 views

Recommender Engine for documents VS Search engine indexing

I have a lot of books and I want to make recommendations to users based on the description and the title of those books. I think that one way is to preprocess the content of the title and ...
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39 views

How does amazon book orders by feature?

Note: I'm not sure if this is the right place to ask, but I don't know any other places. If you know other places which are more proper for this question, please tell me. For example, for this link. ...
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136 views

What does ItemAverage Recommender do in Mahout

The description sounds to me as if it makes a MostPopular recommendation. But the MostPopular recommendation I did myself got much better results. So what does this recommender really return? It is a ...

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