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abbreviation to define
  

Examples: NFL, NASA, PSP, HIPAA, random
Word(s) in meaning: chat  "global warming"
Postal codes: USA: 81657, Canada: T5A 0A7

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What does CB stand for?

Collaborative Filtering


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This definition appears very rarely and is found in the following Acronym Finder categories:

  • Science, medicine, engineering, etc.

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Coated Back (paper)
Cobra Ball
COBRA BRASS
Code Block
Code Blue
Code Breaker
Coffee Break
Cold Beer
ColdBlood (game)
Coldwell Banker
Collapsing Buffer
Collector Books (Paducah, KY)
College Board
Collettore Benzina (automotive; fuel collector)
Colorbar
Columbium (old name for Niobium)
Come-Back
Comment Back
Commercial Bank (various locations)
Common Bantu



Samples in periodicals archive:
Systems like the auto-tagging music algorithms developed at UCSD could be useful in filling in the "blind spots" in Genius and other collaborative filtering systems that rely on the wisdom of the masses to generate playlists.
In its contextual form, the system can mine the data using collaborative filtering techniques to provide personalized recommendations of web sites to an individual user.
A sampling of topics: the mechanism design of traffic BOT (build, operate, and transfer) project auction, laws on support counts of apriori algorithm candidates, a peer-to-peer based distributed collaborative filtering architecture, a precontract-based transaction handing method in workflow, a production management system for clothing enterprises, and a distance measurement system based on binocular stereo vision.
Video Island and its branded partners use what is known as collaborative filtering software, which builds up a profile of the consumer's likes and dislikes and then makes recommendations.
In its contextual form, the system can mine the data using collaborative filtering techniques to provide personalized recommendations of web sites to an individual user.
The result is a kind of real- time collaborative filtering and customer feedback loop, based on the premise that what customers do is just as important as what they say.
In a third recent case in collaboration with a leading academic institution, Pervasive deployed Pervasive DataRush to model customer behavior for a different, extended recommender system with content-based and collaborative filtering.
Written for students and practitioners of information science, cognitive science and computer science, these articles cover a wide range of CSIRA topics such as improved user modeling through applications such as DemonD and COBRAS, adaptations to users of mobile technologies, adaptive user profiles and computing recommendations with collaborative filtering.

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