Using GHSOM to construct legal maps for Taiwan’s securities and futures markets

Shih, Jen-Ying; Chang, Yu-Jung; Chen, Wun-Hwa

doi:10.1016/j.eswa.2006.10.031

Cited by 24 publications

(7 citation statements)

References 21 publications

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“…Due to the flexible and hierarchical nature the GHSOM is capable to extract even more complex clustering with a very faster training process. GHSOMs have been adopted in many fields, including image recognition (Palomo et al, 2009(Palomo et al, , 2013, marketing (de Brito and Oliveira, 2012;, finance (Huang et al, 2014), text mining (Shih et al, 2008), data mining (Soriano-Asensi et al, 2008), Time series (Hsu and Chen, 2014), network security (Zolotukhin et al, 2013), and in other emerging areas of research.…”

Section: Jeim 284mentioning

confidence: 99%

Examining mobile based payment services adoption issues

Upadhyay

Chattopadhyay

2015

Journal of Enterprise Information Management

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Purpose – The purpose of this paper is to make a unified approach in identifying the issues affecting usage intention of mobile-based payment services. The work aims to analyze the reduced factors from data obtained from a survey to highlight the influencers of usage intention mobile-based payment in an integrated manner by incorporating the technical characteristics, technology-specific characteristics, user-specific characteristics and task-specific characteristics. Design/methodology/approach – A nationwide primary survey was conducted using validated questionnaire requesting response for 11 factors obtained from published literature. In all, 196 respondents participated in the survey in India. Valid responses were analyzed using Growing Hierarchical Self-Organizing Map (GHSOM) model. The interactive GHSOM application was applied to automatically determine the filtering rules for clustering. Findings – The hierarchical structure of clusters as obtained by applying GHSOM is mainly influenced by factors like innovativeness, discomfort, system quality, perceived usefulness, perceived ease of use, task-fit, connectivity, absorptive capacity and structural assurance. Research limitations/implications – Increasing trend of online and mobile-based payment has been observed and reported by several studies in India. The frequency of online transactions by women have shown a steady increase over a short period of time. But the survey obtained higher percentage of data from males. Thus future researchers could focus on this aspect to study the influence of this rising trend on adoption of services like mobile-based payment. Trust and existence of physical institutions seem to affect the perception and usage intention. Future researchers may explore the influence of these two issues in situations where there has been some reported cases of breach of trust. Originality/value – There has been very few studies conducted which reported mobile-based transfer payment adoption issues where-in the transfer mechanism is independent of formal banking. Also no other study adopted the GHSOM approach to analyze the data. The findings would be beneficial for service providers of mobile-based payment services to understand their subscribers and roll out value-added services.

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Section: Jeim 284mentioning

confidence: 99%

Examining mobile based payment services adoption issues

Upadhyay

Chattopadhyay

2015

Journal of Enterprise Information Management

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“…• Problems related to their statistical topology and their inability to represent the hierarchical relationships in the input data [30][31][32][33][34][35].…”

Section: The Som and Ghsommentioning

confidence: 99%

Using Fuzzy Logic Algorithms and Growing Hierarchical Self-Organizing Maps to Define Efficient Security Inspection Strategies in a Container Terminal

Morales¹,

Onieva²,

Pérez³

et al. 2020

IJCIS

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Maritime transport is one of the oldest methods of moving various types of goods, and it continues to have an important role in our modern society. More than 20 million containers are transported across the oceans daily. However, this form of transportation is constantly threatened by illegal operations, such as the smuggling of goods or people and merchandise theft. Port security departments must be prepared to face the different threats and challenges that accompany the use of innovative techniques and devices to achieve efficient inspection strategies. Two inspection strategies are presented in this study. The first strategy is based on fuzzy logic (FL), and the second strategy is based on the growing hierarchical self-organizing map (GHSOM) approach. The weight variation and security index (SI) of a container and the readings from certain technologies, such as radio-frequency identification (RFID) and X-ray scanning, are considered as the input data. To minimize the inspection time and considering the costs associated with the security inspections of containers, the results of both inspection strategies are compared and analyzed.The findings indicate there is potential for improving the effectiveness of security inspections by employing both techniques, and the specific relevance in the case of GHSOMs is discussed.

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“…To address the weaknesses of SOMs, including the predefined and fixed topology size and the inability to identify hierarchical relations among samples, Dittenbach, Merkl, and Rauber [12] developed the concept of a GHSOM, which addresses the issue of the fixed network architecture of an SOM through a multilayer hierarchical network structure. The flexible and hierarchical features of a GHSOM generate more delicate clustering results than an SOM and make a GHSOM a versatile analysis tool for tasks regarding data mining, image recognition, Web mining, and text mining problems [12,13,38,41,43,46,50]. Tsaih et al [46] used GHSOM to cluster preliminarily non-fraud and fraud financial statements into subgroups with hierarchical relationships.…”

Section: Studymentioning

confidence: 99%

Feature Extraction of Fraudulent Financial Reporting Through Unsupervised Neural Networks

Huang¹,

Tsaih²,

Lin³

2014

NNW

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This tutorial is based on modification of the professor nomination lecture presented two years ago in front of the Scientific Council of the Czech Technical University in Prague [16].It is devoted to the techniques for the models developing suitable for processes forecasting in complex systems. Because of the high sensitivity of the processes to the initial conditions and, consequently, due to our limited possibilities to forecast the processes for the long-term horizon, the attention is focused on the techniques leading to practical applications of the short term prediction models. The aim of this tutorial paper is to bring attention to possible difficulties which designers of the predicting models and their users meet and which have to be solved during the prediction model developing, validation, testing, and applications. The presented overview is not complete, it only reflects the author's experience with developing of the prediction models for practical tasks solving in banking, meteorology, air pollution and energy sector. The paper is completed by an example of the global solar radiation prediction which forms an important input for the electrical energy production forecast from renewable sources. The global solar radiation forecasting is based on numerical weather prediction models. The time-lagged ensemble technique for uncertainty quantification is demonstrated on a simple example.

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Using GHSOM to construct legal maps for Taiwan’s securities and futures markets

Cited by 24 publications

References 21 publications

Examining mobile based payment services adoption issues

Examining mobile based payment services adoption issues

Using Fuzzy Logic Algorithms and Growing Hierarchical Self-Organizing Maps to Define Efficient Security Inspection Strategies in a Container Terminal

Feature Extraction of Fraudulent Financial Reporting Through Unsupervised Neural Networks

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