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A necessary preprocessing of document classification is to label some documents so that a classifier can be built based on which the remaining documents can be classified. Because each document differs in length and complexity, the cost of labeling each document is different. The purpose of this paper is to consider how to select a subset of documents for labeling with a limited budget so that the total cost of the spending does not exceed the budget limit, while at the same time building a classifier with the best classification results.

In this paper, a framework is proposed to select the instances for labeling that integrate two clustering algorithms and two centroid selection methods. From the selected and labeled instances, five different classifiers were constructed with good classification accuracy to prove the superiority of the selected instances.

Experimental results show that this method can establish a training data set containing the most suitable data under the premise of considering the cost constraints. The data set considers both “data representativeness” and “data selection cost,” so that the training data labeled by experts can effectively establish a classifier with high accuracy.

No previous research has considered how to establish a training set with a cost limit when each document has a distinct labeling cost. This paper is the first attempt to resolve this issue.

The purpose of this study is to identify the factors that influence the development of service robots, and to apply a service innovation strategic mindset to the hotel industry in Taiwan.

A mixed-methods approach, combining an expert panel and semi-structured interviews using a SMART SWOT ranking survey, was applied to understand the perspectives of hotel owners and robotics experts.

Fifty-three items were collected regarding the demand side of the hospitality market, showing that the Taiwan hospitality industry has good potential to implement service robots. Sixty-one items on the supply side of business were collected, showing that this robotics service can help hotels handle seasonal employment and labor utilization. The SWOT analysis identifies “The fun and curiosity aroused in consumers can enhance the promotion of service robots”, “Lack of talent in system integration”, “Taiwan’s aging society can increase the demand for service robots” and “China and South-east countries have aggressively poached talent in the global robotics market” as key issues.

Few studies have investigated robotics service for hotels using the six-dimensional service innovation model. This model helps identify six factors and implies that this new service concept can position hotels to better compete by using IT and relationship marketing strategies.

This study explores the career trajectories of Chief Executive Officers (CEOs) to uncover unique characteristics that contribute to their success. By utilizing web scraping and machine learning techniques, over two thousand CEO profiles from LinkedIn are analyzed to understand patterns in their career paths. This study offers an alternative approach compared to the predominantly qualitative research methods employed in previous research.

This study proposes a framework for analyzing CEO career patterns. Job titles and company information are encoded using the Standard Occupational Classification (SOC) scheme. The study employs the Needleman-Wunsch optimal matching algorithm and an agglomerative approach to construct distance matrices and cluster CEO career paths.

This study gathered data on the career transition processes of graduates from several renowned public and private universities in the United States via LinkedIn. Employing machine learning techniques, the analysis revealed diverse career trajectories. The findings offer career guidance for individuals from various academic backgrounds aspiring to become CEOs.

The building of a career sequence that takes into account the number of years requires integers. Numbers that are not integers have been rounded up to facilitate the optimal matching process but this approach prevents a perfectly accurate representation of time worked.

This study makes an original contribution to the field of career pattern analysis by disclosing the distinct career path groups of CEOs using the rich LinkedIn online dataset. Note that our CEO profiles are not restricted in any industry or specific career paths followed to becoming CEOs. In light of the fact that individuals who hold CEO positions are usually perceived by society as successful, we are interested in finding the characteristics behind their success and whether either the title held or the company they remain at show patterns in making them who they are today.

As a matter of fact, nearly all CEOs had previous experience working for a non-Fortune organization before joining a Fortune company. Of those who have worked for Fortune firms, the number of CEOs with experience in Fortune 500 forms exceeded those with experience in Fortune 1,000 firms.

Outlines the definitions of harassment and discrimination and then details ways in which any case should be treated. Advocates the need for clear and specific company policies as a preventative measure and the need for claims to be dealt with in a professional manner.

This paper aims to study the impacts of groundwater seepage on artificial freezing process of gravel strata, the temperature field characteristics of the strata, and the strata process, closure time and thickness evolution mechanism of the frozen wall.

In this paper several laboratory model tests were conducted, considering different groundwater seepage rate.

The results show that there is a significant coupling effect between the cold diffusion of artificial freezing pipes and groundwater seepage; when there is no seepage, temperature fields upstream and downstream of the gravel strata are symmetrically distributed, and the thickness of the frozen soil column/frozen wall is consistent during artificial freezing; groundwater seepage causes significant asymmetry in the temperature fields upstream and downstream of the gravel strata, and the greater the seepage rate, the more obvious the asymmetry; the frozen wall closure time increases linearly with the increase in the groundwater seepage rate, and specifically, the time length under seepage rate of 5.00 m d⁻¹ is 3.2 times longer than that under no seepage; due to the erosion from groundwater seepage, the thickness of the upstream frozen wall decreases linearly with the seepage velocity, while that of the downstream frozen wall increases linearly, resulting in a saddle-shaped frozen wall.

The research results are beneficial to the optimum design and risk control of artificial freezing process in gravel strata.

Global building failures, such as the Grenfell Tower fire in London, UK, emphasised the need for trustworthy building handover information for safety. However, a notable gap remains in understanding how reliable handover information can ensure the safety of occupants. This study aims to investigate the use and essential quality of handover information to understand the effects of the quality of information on the management of commercial buildings.

Ninety-four participants from nine organisations who regularly use handover information to manage multiple commercial buildings participated in the semi-structured interviews. Qualitative thematic coding using interview transcripts was performed to identify the utilisation of handover information and its quality requirements.

This study reveals that as-built drawings and product information are predominately used to fulfil statutory obligations, comply with the organisation’s internal policies, evaluate asset valuation and make informed decisions about capital investment and operating expenses. The quality dimensions of “accuracy”, “timeliness”, and “completeness” are preferred in combination to achieve desired outcomes.

This study focused on using handover information in the management of commercial buildings. However, its results can offer valuable perspectives for improving its application across various sectors in the built environment.

The findings affirm the need for quality handover information for safety, compliance and efficient management in commercial buildings.

This research significantly contributes to the current knowledge of handover information in the building sector. Given the study findings, building owners are equipped to define specific handover information requirements and quality requisites.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

The purpose of this paper is to explore the structural relationship between experiential loyalty and its seven drivers – interaction quality, physical environment quality, outcome quality, affective quality, experiential quality, experiential trust and experiential satisfaction in the context of Islamic banks.

The data used in this study were based on a convenience sample of 474 respondents from Jakarta, Bogor and Depok in Indonesia.

Interaction quality, physical environment quality and outcome quality positively influence experiential quality, which in turn, leads to experiential trust. Also, experiential trust has a positive influence on experiential satisfaction. Both experiential trust and experiential satisfaction are determinants of experiential loyalty.

The results will assist Islamic bank management in developing and implementing market-orientated service strategies to increase interaction quality, physical environment quality, outcome quality, affective quality experiential quality, experiential trust and experiential satisfaction in order to increase experiential loyalty.

This paper provides data that result in a better understanding of the relationships among interaction quality, physical environment quality, outcome quality, affective quality, experiential quality, experiential trust, experiential satisfaction and experiential loyalty in the context of Islamic banks.