Hybrid recommendation using temporal data for accuracy improvement in item recommendation
Recommender systems have become a vital entity to the business world in form of software tools to make decisions. It estimates the overloaded information and provides the suitable decisions in any kind of business work through online. Especially in the area of e-commerce, recommender systems provide...
| Permalink: | http://skupni.nsk.hr/Record/nsk.NSK01001136760/Details |
|---|---|
| Matična publikacija: |
Journal of information and organizational sciences (Online) 45 (2021), 2 ; str. 535-551 |
| Glavni autori: | Parasuraman, Desabandhu (Author), Elumalai, Sathiyamoorthy |
| Vrsta građe: | e-članak |
| Jezik: | eng |
| Predmet: | |
| Online pristup: |
https://doi.org/10.31341/jios.45.2.10 Elektronička verzija članka Hrčak |
| LEADER | 02376naa a22003494i 4500 | ||
|---|---|---|---|
| 001 | NSK01001136760 | ||
| 003 | HR-ZaNSK | ||
| 005 | 20220630153854.0 | ||
| 006 | m d | ||
| 007 | cr|||||||||||| | ||
| 008 | 220503s2021 ci d |o |0|| ||eng | ||
| 024 | 7 | |2 doi |a 10.31341/jios.45.2.10 | |
| 035 | |a (HR-ZaNSK)001136760 | ||
| 040 | |a HR-ZaNSK |b hrv |c HR-ZaNSK |e ppiak | ||
| 042 | |a croatica | ||
| 044 | |a ci |c hr | ||
| 080 | 1 | |a 004 |2 2011 | |
| 100 | 1 | |a Parasuraman, Desabandhu |4 aut |9 HR-ZaNSK | |
| 245 | 1 | 0 | |a Hybrid recommendation using temporal data for accuracy improvement in item recommendation |h [Elektronička građa] / |c Desabandhu Parasuraman, Sathiyamoorthy Elumalai. |
| 300 | |b Graf. prikazi. | ||
| 504 | |a Bibliografske bilješke na kraju teksta. | ||
| 504 | |a Abstract. | ||
| 520 | |a Recommender systems have become a vital entity to the business world in form of software tools to make decisions. It estimates the overloaded information and provides the suitable decisions in any kind of business work through online. Especially in the area of e-commerce, recommender systems provide suggestions to users on the items that are likely based upon user"s true interest. Collaborative Filtering and Content Based Filtering are the main techniques of recommender systems. Collaborative Filtering is considered to be the best in all domains and always outperforms Content Based filtering. But, both the techniques have some limitations like data sparsity, cold start, gray sheep and scalability issues. To overcome these limitations, Hybrid Recommender Systems are used by combining Collaborative Filtering and Content Based Filtering. This paper proposes such kind of hybrid system by combining Collaborative Filtering and Content Based Filtering using time variance and machine learning algorithm. | ||
| 653 | 0 | |a Softverski alati |a Donošenje odluka |a Sustavi za davanje preporuka |a Strojno učenje | |
| 700 | 1 | |a Elumalai, Sathiyamoorthy |4 aut |9 HR-ZaNSK | |
| 773 | 0 | |t Journal of information and organizational sciences (Online) |x 1846-9418 |g 45 (2021), 2 ; str. 535-551 |w nsk.(HR-ZaNSK)000672813 | |
| 981 | |b Be2021 |b B02/21 | ||
| 998 | |b tino2206 | ||
| 856 | 4 | 0 | |u https://doi.org/10.31341/jios.45.2.10 |
| 856 | 4 | 0 | |u https://jios.foi.hr/index.php/jios/article/view/1626 |y Elektronička verzija članka |
| 856 | 4 | 1 | |y Digitalna.nsk.hr |
| 856 | 4 | 0 | |u https://hrcak.srce.hr/270714 |y Hrčak |