Probabilistic Matrix Factorization Based Collaborative Filtering: Implicit Trust Derived From Review Ratings Information - Eda Ercan
-40% koodiga BOOKS
Saadetis 12-18 tööpäeva jooksul
30-päevane tagastamisõigus
Recommender systems aim to suggest relevant items that are likely to be of interest to the users using a variety of information resources such as user profiles, trust information and users past predictions. However, typical recommender systems suffer from poor scalability, generating incomprehensible and not useful recommendations and data sparsity problem.In this work, we have proposed a probabilistic matr ... Täielik kirjeldus
Võib-olla meeldib sulle ka
TOP
Gödel, Escher, Bach: An Eternal Golden Braid
-40% koodiga BOOKS
Meie tarnija laos
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
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
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
Hackers. 25th Anniversary Edition: Heroes of the Computer Revolution
-40% koodiga BOOKS
Meie tarnija laos
TOP
Proofs from THE BOOK
Martin Aigner, Günter M. Ziegler
-40% koodiga BOOKS
Meie tarnija laos
Kirjeldus
Recommender systems aim to suggest relevant items that are likely to be of interest to the users using a variety of information resources such as user profiles, trust information and users past predictions. However, typical recommender systems suffer from poor scalability, generating incomprehensible and not useful recommendations and data sparsity problem.In this work, we have proposed a probabilistic matrix factorization based local trust boosted recommendation system which handles data sparsity, scalability and understandability problems. The method utilizes the implicit trust in the review ratings of users. The experiments conducted on Epinions.com dataset showed that our method compares favorably with the methods in the literature.In the scope of this work, we have analyzed the effect of latent vector initialization in matrix factorization models; different techniques are compared with the selected evaluation criteria.
Lisateave
| Autor | Eda Ercan |
|---|---|
| Kirjastaja | LAP LAMBERT Academic Publishing |
| Väljalaskeaasta | 2011 |
| Kaanetüüp | Pehme kaanega |
| EAN | 9783846597545 |