Similarity Function With Temporal Factor In Collaborative Filtering: Data Mining - Meghna Khatri,Chhavi Rana
-40% koodiga BOOKS
Saadetis 12-18 tööpäeva jooksul
30-päevane tagastamisõigus
Similarity function is the key to accuracy of collaborative filtering algorithms. Adding a time factor to it addresses the problem of handling the web data efficiently as it is highly dynamic in nature. The data used in collaborative filtering algorithms is collected over as long period of time, in the form of feedbacks, clicks, etc. The interest of user or popularity of an item tends to change as new seaso ... Täielik kirjeldus
Võib-olla meeldib sulle ka
TOP
If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All
Eliezer Yudkowsky, Nate Soares
-40% koodiga BOOKS
Meie tarnija laos
TOP
Gödel, Escher, Bach: An Eternal Golden Braid
-40% koodiga BOOKS
Meie tarnija laos
TOP
AI Engineering: Building Applications with Foundation Models
-40% koodiga BOOKS
Meie tarnija laos
TOP
The Rust Programming Language
Steve Klabnik, Carol Nichols, Chris Krycho
-40% koodiga BOOKS
Meie tarnija laos
TOP
The Art of Game Design: A Book of Lenses
-40% koodiga BOOKS
Meie tarnija laos
TOP
How To Think About AI: A Guide For The Perplexed
-40% koodiga BOOKS
Meie tarnija laos
TOP
Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI
-40% koodiga BOOKS
Meie tarnija laos
TOP
The Pragmatic Programmer: journey to mastery, 20th Anniversary Edition, 2/e: your journey to mastery, 20th Anniversary Edition
-40% koodiga BOOKS
Meie tarnija laos
TOP
HBR Guide to Generative AI for Managers
-40% koodiga BOOKS
Meie tarnija laos
TOP
Hackers. 25th Anniversary Edition: Heroes of the Computer Revolution
-40% koodiga BOOKS
Meie tarnija laos
TOP
The Web Application Hacker's Handbook: Discovering and Exploiting Security Flaws
-40% koodiga BOOKS
Meie tarnija laos
TOP
How Linux Works: What Every Superuser Should Know
-40% koodiga BOOKS
Meie tarnija laos
TOP
Artificial Intelligence: A Modern Approach, Global Edition
-40% koodiga BOOKS
Meie tarnija laos
TOP
Python Crash Course: A Hands-On, Project-Based Introduction to Programming
-40% koodiga BOOKS
Meie tarnija laos
TOP
Fundamentals of Software Architecture: A Modern Engineering Approach
-40% koodiga BOOKS
Meie tarnija laos
TOP
Speak Data: Artists, Scientists, Thinkers, and Dreamers on How We Live Our Lives in Numbers
-40% koodiga BOOKS
Meie tarnija laos
TOP
Linux Basics for Hackers, 2nd Edition: Getting Started with Networking, Scripting, and Security in Kali
-40% koodiga BOOKS
Meie tarnija laos
TOP
C Programming Language
Brian W. Kernighan, Brian Kernighan, Dennis Ritchie
-40% koodiga BOOKS
Meie tarnija laos
TOP
Proofs from THE BOOK
Martin Aigner, Günter M. Ziegler
-40% koodiga BOOKS
Meie tarnija laos
Kirjeldus
Similarity function is the key to accuracy of collaborative filtering algorithms. Adding a time factor to it addresses the problem of handling the web data efficiently as it is highly dynamic in nature. The data used in collaborative filtering algorithms is collected over as long period of time, in the form of feedbacks, clicks, etc. The interest of user or popularity of an item tends to change as new seasons, moods or festivals. The similarity function with temporal factor can efficiently handle the dynamics of web data as it captures and assigns weightage to the data. More recent data is given more weightage when similarity is calculated. in this way, the recent trends and older and obsolete data values are discarded when new unobserved items are predicted using collaborative filtering algorithms. Hence, better results and more accuracy.
Lisateave
| Autor | Meghna Khatri, Chhavi Rana |
|---|---|
| Kirjastaja | LAP LAMBERT Academic Publishing |
| Väljalaskeaasta | 2012 |
| Kaanetüüp | Pehme kaanega |
| EAN | 9783659179952 |