Recommender system

As explained in Graph Algorithms for Data Science

A recommendation system generates ranked or selected items for users based on user, item, or interaction information.

A recommender system generates channel suggestions from existing audience overlap and predicted future relationships between channels. section 10.1

Link prediction can extend recommendations beyond established relationships by identifying channels likely to share audiences in the future. section 10.1

A practical recommendation workflow can:

• Use significant audience overlap to populate existing recommendations. section 10.1
• Calculate several link prediction metrics rather than relying on one similarity score. section 10.1
• Train and evaluate a classification model to forecast future channel relationships. section 10.1

Figure 10.5 Building a link prediction model to recommend Twitch channels

Trace how a link prediction model turns Twitch channel relationships into recommendations. section 10.1

How Graph Algorithms for Data Science covers it

How deep it goes

Explains the workflow through link prediction metrics and classification-model training, without detailing model implementation.

Examples

Uses Twitch channel recommendations and relates the approach to movies, products, and medical concepts.

What it assumes

Assumes an existing shared-audience recommendation system and introduces future-overlap prediction as an extension.

What you can do after

Evaluate recommendation improvements by combining existing relationships with predicted future relationships.

How it connects

Connects recommendation systems with link prediction, audience overlap, similarity metrics, and classification models.

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Also explained in

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  Grokking Machine LearningA recommendation system is a software system that suggests items, content, or actions to users based on available information about them or their context.
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  AI-Powered SearchA software system that infers user interests or behaviors and delivers content or items that it predicts will match them, without requiring an explicit query for each result.
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  Machine Learning Platform EngineeringA recommendation system is a software system that predicts or ranks items, content, or actions for users or other entities.
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  Financial AI in PracticeA software system that generates recommendations from data or predictive models.
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  First-Party Data ActivationA software system that predicts and presents items, content, or actions likely to be relevant to an individual.
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  Causal Inference for Data ScienceA recommender system is a software system that suggests items or actions to users based on available information about them and the items.

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Related concepts

• recommendationproduces · A recommendation is a suggested item, choice, or course of action, based on available information, intended to guide a decision.
• language modelused by · A language model is a computational model that represents patterns in linguistic tokens to estimate sequence probabilities and predict or generate language from context.
• candidate sourcinghas part · Candidate sourcing is the process of identifying potentially suitable candidates from a larger pool for further consideration.
• similarity metricuses · A similarity measure is a rule that quantifies or characterizes how alike two objects or representations are according to selected properties.
• collaborative filteringincludes · Collaborative filtering is a recommendation technique that infers preferences or associations from interaction patterns among users, items, or other entities.
• decision treeused by · A decision tree is a branching structure that represents sequential tests or choices, with paths leading to outcomes, predictions, or actions.

This explainer was generated by Manning's knowledge graph from the text of Graph Algorithms for Data Science. The section links point to the parts of the book it draws on.