Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 505917

Temporal Recommender Systems


Kliček, Božidar; Oreški, Dijana; Begičević, Nina
Temporal Recommender Systems // Recent researches in applied computer and applied computational science / Chen, S ; Mastorakis, Nikos ; Rivas-Echeverria, Francklin ; Mladenov, Valeri (ur.).
Venecija, Italija: WSEAS Press, 2011. str. 248-253 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


CROSBI ID: 505917 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Temporal Recommender Systems

Autori
Kliček, Božidar ; Oreški, Dijana ; Begičević, Nina

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Recent researches in applied computer and applied computational science / Chen, S ; Mastorakis, Nikos ; Rivas-Echeverria, Francklin ; Mladenov, Valeri - : WSEAS Press, 2011, 248-253

ISBN
978-960-474-281-3

Skup
10th WSEAS International Conference on APPLIED COMPUTER and APPLIED COMPUTATIONAL SCIENCE (ACACOS `11)

Mjesto i datum
Venecija, Italija, 08.03.2011. - 10.03.2011

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
temporal customer behavior; consumer satisfaction; data mining; temporal data mining; neural network modeling; temporal recommender systems

Sažetak
This article introduces temporal recommender systems, which are intended for suggesting items in situations where time is an essential factor of the decision-making process. It has been developed on a foundation of empirical research on customer satisfaction and consumption conducted in 12 cafés over a period of 10 days, on a sample consisting of 852 customers, where the time of consumption was recorded. The data was used to create different neural network models for predicting tourist satisfaction and consumption. The results have not only shown variations in customer satisfaction and money spent, in relation to different parameters of consumption, but have also revealed the behavior of different groups of customers in different establishments, competition between different service providers and rivalry between different groups of clients regarding the use of services within the same establishment at the same time. The knowledge thus obtained has been included in a temporal recommender system for visitors of cafés. This system is able to rank and recommend cafés according to predicted customer satisfaction based on their features, cafés’ features, particular circumstances, needs, as well as the time of intended consumption. The basic architecture, possible applications, connection with other scientific topics and suggestions for further research on the subject of temporal recommender systems are given. Possible applications of these models will be essential for the application in dynamic mobile recommender systems.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti



POVEZANOST RADA


Projekti:
016-0161199-0864 - Adaptibilnost visokotehnoloških organizacija (Kliček, Božidar, MZOS ) ( CroRIS)
016-0161217-0769 - Razvoj matematičkih modela za unaprijeđenje kvalitete usluga u javnom sektoru (Hunjak, Tihomir, MZOS ) ( CroRIS)

Ustanove:
Fakultet organizacije i informatike, Varaždin


Citiraj ovu publikaciju:

Kliček, Božidar; Oreški, Dijana; Begičević, Nina
Temporal Recommender Systems // Recent researches in applied computer and applied computational science / Chen, S ; Mastorakis, Nikos ; Rivas-Echeverria, Francklin ; Mladenov, Valeri (ur.).
Venecija, Italija: WSEAS Press, 2011. str. 248-253 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Kliček, B., Oreški, D. & Begičević, N. (2011) Temporal Recommender Systems. U: Chen, S., Mastorakis, N., Rivas-Echeverria, F. & Mladenov, V. (ur.)Recent researches in applied computer and applied computational science.
@article{article, author = {Kli\v{c}ek, Bo\v{z}idar and Ore\v{s}ki, Dijana and Begi\v{c}evi\'{c}, Nina}, year = {2011}, pages = {248-253}, keywords = {temporal customer behavior, consumer satisfaction, data mining, temporal data mining, neural network modeling, temporal recommender systems}, isbn = {978-960-474-281-3}, title = {Temporal Recommender Systems}, keyword = {temporal customer behavior, consumer satisfaction, data mining, temporal data mining, neural network modeling, temporal recommender systems}, publisher = {WSEAS Press}, publisherplace = {Venecija, Italija} }
@article{article, author = {Kli\v{c}ek, Bo\v{z}idar and Ore\v{s}ki, Dijana and Begi\v{c}evi\'{c}, Nina}, year = {2011}, pages = {248-253}, keywords = {temporal customer behavior, consumer satisfaction, data mining, temporal data mining, neural network modeling, temporal recommender systems}, isbn = {978-960-474-281-3}, title = {Temporal Recommender Systems}, keyword = {temporal customer behavior, consumer satisfaction, data mining, temporal data mining, neural network modeling, temporal recommender systems}, publisher = {WSEAS Press}, publisherplace = {Venecija, Italija} }




Contrast
Increase Font
Decrease Font
Dyslexic Font