Difference between revisions of "Recommendation"
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* [[Clustering]] | * [[Clustering]] | ||
* [[AI Solver]] | * [[AI Solver]] | ||
| − | |||
* [http://en.wikipedia.org/wiki/Collaborative_filtering Collaborative Filtering | Wikipedia] | * [http://en.wikipedia.org/wiki/Collaborative_filtering Collaborative Filtering | Wikipedia] | ||
* [http://en.wikipedia.org/wiki/Personalized_marketing Personalized Marketing | Wikipedia] | * [http://en.wikipedia.org/wiki/Personalized_marketing Personalized Marketing | Wikipedia] | ||
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= Recommender Systems = | = Recommender Systems = | ||
| − | * [http://en.wikipedia.org/wiki/Recommender_system Recommender | + | * [http://en.wikipedia.org/wiki/Recommender_system Recommender System | Wikipedia] |
* [http://blog.statsbot.co/recommendation-system-algorithms-ba67f39ac9a3 Recommendation System Algorithms | Daniil Korbut] | * [http://blog.statsbot.co/recommendation-system-algorithms-ba67f39ac9a3 Recommendation System Algorithms | Daniil Korbut] | ||
* [http://www.techemergence.com/business-intelligence-through-intellectual-property-analytics-facebook-amazon/ Business Intelligence Through Intellectual Property Analytics – Examining Facebook and Amazon | Valuenex] | * [http://www.techemergence.com/business-intelligence-through-intellectual-property-analytics-facebook-amazon/ Business Intelligence Through Intellectual Property Analytics – Examining Facebook and Amazon | Valuenex] | ||
Revision as of 23:06, 6 January 2019
Youtube search... ...Google search
- Capabilities
- Clustering
- AI Solver
- Collaborative Filtering | Wikipedia
- Personalized Marketing | Wikipedia
Can items can be directly related to users?
- ... yes, K-Nearest Neighbors (KNN)
- ... no, have a very large dataset, then Alternating Least Squares (ALS)
- ... no, have small to medium dataset, then Matrix Factorization
systems examine attributes of the items recommended. For example, if a Netflix user has watched many cowboy movies, then recommend a movie classified in the datastore as having the “scifi” genre.
systems recommend items based on similarity measures between users and/or items. The items recommended to a user are those preferred by similar users.
Contents
Recommender Systems
- Recommender System | Wikipedia
- Recommendation System Algorithms | Daniil Korbut
- Business Intelligence Through Intellectual Property Analytics – Examining Facebook and Amazon | Valuenex
- Recommendation Systems | Stanford InfoLab
- Introduction To Recommendation system In Javascript | Oni Stephen - Medium
Grouping related items together without labeling them, e.g. grouping patient records with similar symptoms without knowing their symptoms
Building Recommendation Systems in Azure
Azure Machine Learning Studio: Matchbox Recommender
Cortana Analytics: Building a recommendations model
