Hybrid journal (It can contain Open Access articles) ISSN (Print) 1756-7017 - ISSN (Online) 1756-7025 Published by Inderscience Publishers[450 journals]
Authors:Ameni Sassi, Wael Ouarda, Chokri Ben Amar, Serge Miguet Pages: 299 - 327 Abstract: In this paper, we proposed a novel hierarchical two-pathway autoencoders architecture to transform a local information based on skyline scene representation, into nonlinear space. The first pathway is intended for the transformation of the geometric features extracted from the horizon line. The second pathway is applied after the first one to joint the colour information under the skyline to the transformed geometric features, and to get the landscape context conceptualisation. To evaluate our suggested system, we constructed the SKYLINEScene database containing 2,000 images of rural and urban landscapes, with a high degree of diversity. In order to investigate the performance of our HTANN-Skyline, many experiments were carried out using this new database. Our approach shows its robustness in skyline context conceptualisation and enhances the classification rates by 1% compared to the AlexNet architecture; and by more than 10% compared to the hand-crafted approaches based on global and local features. Keywords: deep neural network; autoencoder; scene categorisation; skyline; curvature scale space; features transformation; classification; horizon line; hierarchical; skyline context conceptualisation Citation: International Journal of Information and Decision Sciences, Vol. 12, No. 4 (2020) pp. 299 - 327 PubDate: 2020-10-20T23:20:50-05:00 DOI: 10.1504/IJIDS.2020.110447 Issue No:Vol. 12, No. 4 (2020)
Authors:Sana Hamdi, Emna Bouazizi, Sami Faiz Pages: 348 - 376 Abstract: Nowadays, real-time spatial applications have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of databases and data warehouses especially that users expect to receive the results of each query within a short time period without holding into account the load of the system. To solve this problem, several optimisation techniques are used. Thus, we propose, as a first contribution, a novel data partitioning approach for real-time spatial big data named vertical partitioning approach for real-time spatial big data (VPA-RTSBD). This contribution is an implementation of the matching algorithm for traditional vertical partitioning. Then, as a second contribution, we propose a new frequent itemset mining approach which relaxes the notion of window size and proposes a new algorithm named PrePost*-RTSBD. Thereafter, a simulation study is shown to prove that our contributions can achieve a significant performance improvement. Keywords: real-time spatial data; transaction; stream data; feedback control scheduling; quality of service; data partitioning; frequent itemset mining; simulation Citation: International Journal of Information and Decision Sciences, Vol. 12, No. 4 (2020) pp. 348 - 376 PubDate: 2020-10-20T23:20:50-05:00 DOI: 10.1504/IJIDS.2020.110450 Issue No:Vol. 12, No. 4 (2020)
Authors:Ankit Mehrotra, Reeti Agarwal Pages: 377 - 389 Abstract: Usage of credit cards has been witnessing an increase in recent years in India. The study was undertaken to comprehend the effect of the different demographic characteristics of the respondents on credit cards owned by them. Findings indicate that friends/family members are most influential in affecting customer's knowledge of credit card. It was seen that for pitching more than one credit card, the group of customers that should be targeted are those with low income and in the age group 46-60 years. Keywords: C&RT; credit cards; data mining; demographic variables; feature selection; gender; income; Indian customers; influencing medium; target group Citation: International Journal of Information and Decision Sciences, Vol. 12, No. 4 (2020) pp. 377 - 389 PubDate: 2020-10-20T23:20:50-05:00 DOI: 10.1504/IJIDS.2020.110449 Issue No:Vol. 12, No. 4 (2020)
Authors:Zahra Shekarchizade, Bahram Ranjbarian, Vahid Ghasemi Pages: 390 - 407 Abstract: The aim of this work is to investigate the effect of family structure, duration of family life and family members' acquaintance with travel destination on information search behaviour of heads of families to buy a package tour. A sample of 70 Isfahani heads of families who had bought an outbound package tour in January-September 2017 was selected. The results indicate that family structure and duration of family life have impacts on the perceived value of seeking information among family members. In families that have different value structures and in various stages of family life cycle, the perceived value of seeking information among family members is different; however, the perceived value was not significantly effective in the level of seeking information among family members. Indeed, family members' acquaintance with travel destination has a significant impact on the level of seeking information by using perceived value of seeking information among family members. Keywords: family members; travel information; family structure; duration offamily life; familiarity; information search behaviour; perceived value; familial factors; external source; decision making Citation: International Journal of Information and Decision Sciences, Vol. 12, No. 4 (2020) pp. 390 - 407 PubDate: 2020-10-20T23:20:50-05:00 DOI: 10.1504/IJIDS.2020.110448 Issue No:Vol. 12, No. 4 (2020)
Hybrid journal (It can contain Open Access articles)
[450 journals]
