Web mining + Decision tree recommender
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
- Korea Advanced Institute of Science and Technology (KAIST)
- Organisation type
- Academia
- Country
- Korea (Republic of)
- Published
- 1 October 2002
- Authors
- YH Cho, JK Kim, SH Kim
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
- tokens
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Unknown
- Citations
- 656
Sources
Where this record came from and when it was last checked.
- Reference
- A personalized recommender system based on web usage mining and decision tree induction
- Last updated
- 28 November 2025
What the numbers mean
What this model is
Web mining + Decision tree recommender was published by Korea Advanced Institute of Science and Technology (KAIST), in the country recorded as Korea (Republic of), during October 2002. It comes out of an organisation categorised as academia.
It works in the domain of Recommendation, and is recorded as performing the task of recommender system.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
Web mining + Decision tree recommender — common questions
Web mining + Decision tree recommender— when was it released?
It was published in October 2002. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
Web mining + Decision tree recommender— what is it used for?
It works in the domain of Recommendation, and is recorded as handling the task of 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.
Web mining + Decision tree recommender— what GPU do I need to run it?
None. This 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.
Web mining + Decision tree recommender— is it open source?
The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
Web mining + Decision tree recommender— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
Web mining + Decision tree recommender— who created it?
It was published by Korea Advanced Institute of Science and Technology (KAIST), based in Korea (Republic of), an organisation categorised as academia.
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.