Application of salesman-like recommendation system in 3G mobile phone online shopping decision support

2010 ◽  
Vol 37 (12) ◽  
pp. 8065-8078 ◽  
Author(s):  
Ching-Torng Lin ◽  
Wei-Chiang Hong ◽  
Yi-Fun Chen ◽  
Yucheng Dong
2012 ◽  
Vol 6-7 ◽  
pp. 783-789
Author(s):  
Jian Feng Dong ◽  
Tian Yang Dong ◽  
Jia Jie Yao ◽  
Ling Zhang

With the rapid development of smart-phone applications, how to make the ordering process via smart-phones more convenient and intelligent has become a hotspot. This paper puts forward a method of restaurant dish recommendation relying on position information and association rules. In addition, this paper has designed and developed a restaurant recommendation system based on mobile phone. The system would fetch the real-time location information via smart-phones, and provide customers personalized restaurant and dish recommendation service. According to the related applications, this system can successfully recommend the related restaurants and food information to customers.


2006 ◽  
Vol 12 (1) ◽  
pp. 23-26 ◽  
Author(s):  
Konstantinos A Banitsas ◽  
Konstantinos Perakis ◽  
Sapal Tachakra ◽  
Dimitrios Koutsouris

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Rung-Ching Chen ◽  
Hui Qin Jiang ◽  
Chung-Yi Huang ◽  
Cho-Tsan Bau

Introduction. Although a number of researchers have considered the positive potential of Clinical Decision Support System (CDSS), they did not consider that patients’ attitude which leads to active treatment strategies or HbA1c targets. Materials and Methods. We adopted the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) published to propose an HbA1c target and antidiabetic medication recommendation system for patients. Based on the antidiabetic medication profiles, which were presented by the American Association of Clinical Endocrinologists (AACE) and American College of Endocrinology (ACE), we use TOPSIS to calculate the ranking of antidiabetic medications. Results. The endocrinologist set up ten virtual patients’ medical data to evaluate a decision support system. The system indicates that the CDSS performs well and is useful to 87%, and the recommendation system is suitable for outpatients. The evaluation results of the antidiabetic medications show that the system has 85% satisfaction degree which can assist clinicians to manage T2DM while selecting antidiabetic medications. Conclusions. In addition to aiding doctors’ clinical diagnosis, the system not only can serve as a guide for specialty physicians but also can help nonspecialty doctors and young doctors with their drug prescriptions.


2014 ◽  
Vol 11 (04) ◽  
pp. 1450026 ◽  
Author(s):  
Shwu-Ing Wu ◽  
Li-Pang Ho

As the number of mobile phone users has increased steadily in recent years, mobile phone manufacturers continuously compete to be the first to introduce innovative products to the market in the hope of gaining a larger market share. Currently, the innovation product has become the target of competition in the mobile phone industry. Thus, this study uses 3G mobile phone as an example, through literature review and empirical research to examine whether perceived innovation and brand awareness have a significant impact on the perceived quality, perceived value, and purchase intention toward innovation products. An analysis of 595 effective questionnaires produced five main findings: (i) consumer-perceived innovation has significant and positive impact on the perceived quality and purchase intention; (ii) brand awareness has significant and positive impact on the consumer-perceived quality; (iii) perceived quality has significant and positive impact on perceived value; (iv) consumer-perceived value has significant and positive impact on purchase intention; however, (v) consumer-perceived quality has significant and negative impact on purchase intention. Moreover, this study evidences that consumer-perceived innovation has higher effect on purchase intention than brand awareness. These results can provide useful information to mobile phone industry to carry out innovation planning and marketing strategy.


2016 ◽  
Vol 28 (3) ◽  
pp. 288-298 ◽  
Author(s):  
Hemant Bhargav ◽  
Manjunath N. K. ◽  
Shivarama Varambally ◽  
A. Mooventhan ◽  
Suman Bista ◽  
...  

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