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Questions tagged [recommendation-systems]

Questions about techniques that infer valid or preferred options from existing data with the goal to make helpful suggestions automatically.

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Is Weighted Averages the Best Method to Aggregate Information?

I'm working on a recommendation system. My system uses user's past rating data, to predict future ratings. I designed mathematical methods for generating recommendation algorithms that allows me to ...
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1answer
644 views

Is Supervised Learning Better than Unsupervised Learning (For Recommendation Systems)

I am working on a Recommendation System as a personal project (I finish it on time, I'll present it as my final year project). I devised mathematical methods that estimated User's ratings of products ...
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What are useful/new areas to work on for recommendation systems? [closed]

I am working on a project on recommendation systems, and would like to know about specific areas/research papers on which some new work can be performed, but not something too time/coding intensive. ...
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1answer
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How to compare two objects for percentage of equivalence

I'm trying to create a nodeJS application. It allows users to rate a bunch of songs and it stores them in their user profiles. I use this information to compare them to other users, and try to find ...
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Reasoning approaches for implementing a Knowledge-based System?

What are the major approaches in implementing a Knowledge-based System (KBS)? Approaches used to take decisions in a KBS that I have come across so far are the case-based and rule-based reasoning ...
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2answers
177 views

Relative Importance in Graph Theory [closed]

I am working on an algorithm that ranks a set of nodes in a graph with respect to how relative this node is to other predefined nodes (I call them query nodes). The way how the algorithm works is ...
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1answer
514 views

top-N recommendation in collaborative filtering

I have started to read about user-based and item-based collaborative filtering techniques. I understand how a rating of the target user for a particular item is predicted. How top-N recommendation ...
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262 views

How regression is used in item-based collaborative filtering?

In the paper "Item-Based Collaborative Filtering Recommendation Algorithms" In section 3.2.2 about regression, it is said the the user's actual rating of item N (Ru,n), is replaced with an estimate ...
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Baseline approaches for likes prediction

I have a small user-item matrix (25k x 1.8k) describing how users liked or disliked some of the items. Users don't have any attributes but items have several features. I would like to be able to ...
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Physical Meaning Behind Matrix Factorization

As we all know, Matrix Factorization is an effective method to do rating prediction jobs in recommender systems. Thanks to the work of Yahuda Koren. My question is why MF can do this job? What's the ...
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4answers
3k views

How to devise an algorithm that suggests feasible cooking recipes?

I once had a veteran in my course that created an algorithm that would suggest cooking recipes. At first, all sort of crazy recipes would come out. Then, she would train the cooking algorithm with ...
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How to evaluate recommendation engine without ground truth?

I have developed an algorithm which recommends geographical locations to users based on popular trends and their own interests. The dataset is created by my organization. So the user selects a few ...
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Recommendation algorithms based on a set of attributes

I'm building an application which should suggest products for the users. I want to base my recommendation on different attributes, like location, weather, date, etc. Each of these attributes can have ...