Using an Ontology-Based Neural Network and DEA to Discover Deficiencies of Hotel Services

Chiang, Tzu-An; H., Z.; Huang, Yi-Ling; Tsai, Chang-You

doi:10.4018/ijswis.306748

Cited by 14 publications

(3 citation statements)

References 42 publications

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“…Before the text can be processed, a corpus of documents or collection must undergo some preparation steps. Text preprocessing is the process of converting unstructured data into structured data by applying specific criteria or rules to facilitate future keyword extraction (27) . Some common pre-processing steps include tokenisation, lemmatization, lowercasing, stopwords removal, punctuation mark removal, and reduction of replicated characters (28) .…”

Section: Text Pre-processingmentioning

confidence: 99%

Identifying Terms to Represent Concepts of a Work Process Ontology

Osman,

Noah,

Saad

2024

IJST

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Objectives: To identify ontology concepts from text documents for the construction of work process ontology. Methods: This study proposes a methodology to identify terms representing a work process ontology concept from a document. The methodology encompasses several key steps: document collecting, text pre-processing, term weighting and analysis, terms mapping, and domain expert relevance judgments. A comparison between the results of three different term weighting schemes, namely the Term Frequency (TF), Term Frequency-Inverse Document Frequency (TFIDF), and Mutual Information (MI) is made with the ontology concept that the domain expert has judged. Findings: The approaches adopted in this study have managed to extract ontological concepts from the targeted domain knowledge source. The findings of the comparison analysis suggest that the TFIDF term weighting scheme exhibits better results compared to the TF and MI weighting schemes. Novelty: A work process ontology is a structured knowledge describing daily operations in the government sector. However, there has been little to no effort in building the work process ontology. This study presents an integrated approach for identifying ontology concepts from documents within the domain of the work process. To the utmost extent of our understanding, this research initiative is the initial attempt to introduce a structured methodology for the semi-automatic extraction and evaluation of concepts and relationships within this domain. The findings can be utilised as a foundation for developing an ontology in the specific field. Keywords: Ontology, Work process, Text extraction, Natural language processing, Term weighting

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Section: Text Pre-processingmentioning

confidence: 99%

Identifying Terms to Represent Concepts of a Work Process Ontology

Osman,

Noah,

Saad

2024

IJST

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“…Some scholars have used big data to classify color matching schemes [53][54][55][56][57][58]. Research has also been conducted using cloud computing, neural networks, and other method applications in hotel service social media to improve the user experience [59][60][61]. Among them, other application methods have reference value for color emotion research, which can be applied in future research.…”

Section: Plos Onementioning

confidence: 99%

The visual design of urban multimedia portals

Wang

Zhang²

2023

PLoS ONE

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In the visual design of a portal website, color is the first intuitive factor for users. It is relatively difficult for the designer of a city portal website to choose a color system that represents a city’s unique color from among the many available options. Therefore, this study extracted a decision-making model of the urban color system, which can help decision-makers and designers choose among color systems, and then effectively design a portal website that conforms to local cultural attributes. The proposed method to solve the problem involved obtaining optimal color matching by performing weight analysis of colors through 123 sample color semantics, factor analysis, and a fuzzy analytic hierarchy process. Semantic analysis was used to classify colors into four categories of fashion, technology, calm, and dazzling. The fashion color matching scheme scored relatively high. Web page color matching schemes with a white background were popular, among which a white and green color matching scheme scored relatively high. At the same time, there are differences in color preferences between genders and cultures. This study is significant because it proposes a color decision model for portal websites, which provides a reference value that can also be applied to the selection of color schemes for other types of web pages in the future.

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“…NNs have been widely applied to data processing (Srivastava et al, 2022;Hasib, Towhid & Islam, 2021;Pradhan et al, 2022), pattern classification and recognition (Chiang et al, 2022;Hammad et al, 2021;Yen, Moh & Moh, 2021), and blockchain technology (Nguyen et al, 2021) owing to their strong learning and approximation capability. For an unknown continuous nonlinear function g K ( ) : , , ] 1 2  and l s are the weights of neural networks, and s > 1 indicates neural cell numbers.…”

Section: Neural Networkmentioning

confidence: 99%

Neuro-Based Consensus Seeking for Nonlinear Uncertainty Multi-Agent Systems Constrained by Dead-Zone Input

Qin,

Gai

2023

International Journal on Semantic Web and Information Systems

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The topic about consensus target track seeking for high-order nonlinear multi-agent systems (MASs) with unmodeled dynamics, dynamic disturbances, and dead-zone input is considered in the paper. Using the strong nonlinear map characteristic of radial basis function neural networks (RBFNNs), the complex functions arising from recursive procedure are simplified. Also, inspired by input-to-state practical stability (ISpS), the authors construct a dynamical signal in order to counteract the impact of unmodeled dynamics and dynamic disturbances. The bounded inequality expression has been applied to tackle the unknown input of dead zone. Based on this, consensus control protocol suitable for nonlinear constraints has been constructed by using the recursive backstepping technique and adaptive neural network method. Theoretical analysis indicates not only the uniform boundary of all signals in the closed-loop under the neuro-based consensus controller, but uniform ultimate convergence of consensus tracking errors. The final simulations also confirmed the correctness of the theoretical analysis.

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Using an Ontology-Based Neural Network and DEA to Discover Deficiencies of Hotel Services

Cited by 14 publications

References 42 publications

Identifying Terms to Represent Concepts of a Work Process Ontology

Identifying Terms to Represent Concepts of a Work Process Ontology

The visual design of urban multimedia portals

Neuro-Based Consensus Seeking for Nonlinear Uncertainty Multi-Agent Systems Constrained by Dead-Zone Input

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