Enhanced Neighborhood-Based Filtering
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- AT&T
- Organisation type
- Industry
- Country
- United States of America
- Published
- 28 October 2007
- Authors
- RM Bell, Y Koren
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Recommendation
- Task
- Recommender system
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Training data
- 100,000,000 tokens
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Why it is tracked
- SOTA improvement
- Record confidence
- Unknown
- Citations
- 687
"We evaluate these methods on the Netflix dataset, where they deliver significantly better results than the commercial Netflix Cinematch recommender system." they don't claim absolute SOTA on any of the benchmarks
Sources
Where this record came from and when it was last checked.
- Reference
- Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
Enhanced Neighborhood-Based Filtering was published by AT&T, in United States of America, in October 2007. It comes out of industry.
It works in Recommendation, and is recorded as doing recommender system.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
What went into building it
It was trained on about 100,000,000 tokens of text.
Its inclusion criterion is sOTA improvement.
Answers
Enhanced Neighborhood-Based Filtering — common questions
What GPU do I need to run Enhanced Neighborhood-Based Filtering?
None. Enhanced Neighborhood-Based Filtering is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
Is Enhanced Neighborhood-Based Filtering open source?
The licensing for Enhanced Neighborhood-Based Filtering was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does Enhanced Neighborhood-Based Filtering have?
No parameter count has been published for Enhanced Neighborhood-Based Filtering, which is why no memory or speed figure appears on this page.
Who created Enhanced Neighborhood-Based Filtering?
Enhanced Neighborhood-Based Filtering was published by AT&T, based in United States of America, categorised as industry.
When was Enhanced Neighborhood-Based Filtering released?
Enhanced Neighborhood-Based Filtering was published in October 2007. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is Enhanced Neighborhood-Based Filtering used for?
Enhanced Neighborhood-Based Filtering works in Recommendation, and is recorded as handling recommender system. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.