Pattern mining in tourist attraction visits through association rule learning on Bluetooth tracking data: A case study of Ghent,Belgium

The rapid evolution of information and positioning technologies, and their increasing adoption in tourism management practices allows for new and challenging research avenues. This paper presents an empirical case study on the mining of association rules in tourist attraction visits, registered for 15 days by the Bluetooth tracking methodology. This way, this paper aims to be a methodological contribution to the field of spatiotemporal tourism behavior research by demonstrating the potential of ad-hoc sensing networks in the non-participatory measurement of small-scale movements. An extensive filtering procedure is followed by an exploratory analysis, analyzing the discovered associations for different visitor segments and additionally visualizing them in ‘visit pattern maps’. Despite the limited duration of the tracking period, we were able to discover interesting associations and further identified a tendency of visitors to rarely combine visits in the center with visits outside of the city center. We conclude by discussing both the potential of the employed methodology as well as its further issues.     

Tourism-based heritage conservation in Murshidabad: an appraisal

The article appraises the outcome of promoting tourism as a strategy for heritage conservation in the case of Murshidabad, an archetypal historic town in decline in India. A relational maturity-based framework has been used to examine the complementarities and conflicts between tourism and heritage conservation in the town. The prevailing nature of tourism conservation relationship in Murshidabad upholds the criticality characteristically observed in developing countries, where governments focus primarily on the revenue generating potential of built-heritage centric tourism ignoring the conservation attention necessary to retain authenticity and meaningful existence of historic structures. The overarching issues emerging from the current level of relational maturity in Murshidabad are identified with suggestions for possible policy implications of the study.     

确定采矿及建筑施工排水水资源费征收标准的理论方法

在分析排水水资源费的本质、排水与取水水资源费确定方法异同点的基础上,提出理论上排水水资源费征收标准的2种确定方法,即直接利用取水水资源费征收标准进行修正的方法和排水水资源费的边际机会成本法。同时分析目前我国地方省份采矿及建筑施工排水水资源费征收标准的特点,并利用提出的2种排水水资源费征收标准的确定方法分析产生这些特点的原因,论证有些地方省份排水水资源费征收标准高于取水水资源费征收标准的缘由。     

Intelligent agents for adaptive security market surveillance

Market surveillance systems have increasingly gained in usage for monitoring trading activities in stock markets to maintain market integrity. Existing systems primarily focus on the numerical analysis of market activity data and generally ignore textual information. To fulfil the requirements of information-based surveillance, a multi-agent-based architecture that uses agent intercommunication and incremental learning mechanisms is proposed to provide a flexible and adaptive inspection process. A prototype system is implemented using the techniques of text mining and rule-based reasoning, among others. Based on experiments in the scalping surveillance scenario, the system can identify target information evidence up to 87.50% of the time and automatically identify 70.59% of cases depending on the constraints on the available information sources. The results of this study indicate that the proposed information surveillance system is effective. This study thus contributes to the market surveillance literature and has significant practical implications.     

Does Size Matter? Evaluating Corporate Environmental Disclosure in the Australian Mining and Metal Industry: A Combined Approach of Quantity and Quality Measurement

There are an increasing number of companies in the mining and metals sector disclosing environmental sustainability information in their annual reports, sustainability reports and corporate internet web pages. However, there is ongoing debate about the relationship between the quantity and the quality of environmental disclosure. That is, does an increase in number equate to an increase in quality? This study investigates the relationship between the quantity and the quality of environmental disclosure reports. Using content analysis, we examine the environmental disclosure of 55 Australian mining and metal companies which are listed among the Australian Securities Exchange's (ASX) Top 100 mining and metal sector companies. We find that the size of firms influences both the quantity and the quality of corporate environmental disclosure. That is, we find that market capitalization is positively and significantly correlated to the quantity (number of words) and the quality of disclosure. We also confirm that there is a very highly significant, positive correlation between quantity (number of words) and quality of environmental disclosure. In order to investigate any differences between the top performing group and the bottom performing group in terms of environmental disclosure quality, further analysis also confirms that there is a positive relationship between the quantity and the quality of environmental disclosure. Copyright © 2015 John Wiley & Sons, Ltd and ERP Environment     

Data mining framework based on rough set theory to improve location selection decisions: A case study of a restaurant chain

Location selection plays a crucial role in the retail and service industries. A comprehensive location selection model and appropriate analytical technique can improve the quality of location decisions, attracting more customers and substantially impacting market share and profitability. This study developed a data mining framework based on rough set theory (RST) to support location selection decisions. The proposed framework consists of four stages: (1) problem definition and data collection; (2) RST analysis; (3) rule validation; and (4) knowledge extraction and usage. An empirical study focused on a restaurant chain to demonstrate the validity of the proposed approach. Twenty location variables relevant to five location aspects were examined, and the results indicated that latent knowledge can be identified to support location selection decisions.     

高职学生问题解决能力培养途径研究——以江苏经贸职业技术学院为例

培养大学生的问题解决能力,是提高大学生综合素养的重要手段.以江苏经贸职业技术学院为例,分析目前高职学生问题解决能力的现状、面临的主要问题及处理问题的方式,研究高职学生问题解决能力的培养模型及主要途径.     

建筑装饰工程施工管理中存在的问题及解决办法探讨

本文就建筑装饰工程管理中存在的问题提出了一些相应的解决措施。     

论数字挖掘技术在图书馆借阅系统中的应用

本文论述了数据挖掘技术在图书馆借阅系统的应用,通过对原有管理系统现有数据的整理统计,对满足要求的数据使用K-means算法进行分割,由分类后的数据可以合理地调整不同读者群的流通图书借阅方法,优化图书资源的使用状况。     

Customer relationship management in retailing: A content analysis of retail trade journals

The purpose of this research was to increase knowledge and understanding of how retailers use business intelligence and data mining tools to implement customer relationship management (CRM) in retailing. Specific objectives were to (1) identify organization and infrastructure requirements for CRM effectiveness, (2) identify CRM objectives and goals of retail companies, (3) identify data mining tools utilized by retailers to perform CRM functions, and (4) identify CRM strategies used by retail companies. A keyword search within business databases using CRM and CRM identified publications with CRM content. Content analysis was used on articles (N=149) drawn from Stores, Chain Store Age, Harvard Business Review, and Retail Forward over a 5 year period (2000–2005). Selected articles were stored as text files in QDA Miner, a computerized qualitative analysis tool. Key organization/infrastructure needs emerged focusing on data structure, organizational systems, technology structure, and data accessibility. Retailers goals/objectives and strategies focused on marketing, customer service, understanding customers through data analysis and increasing acquisition and retention through customer loyalty programs. Data mining tools identified supported marketing and customer analysis efforts. Findings provide insight into the challenges retailers face as they implement a more customer-centric business strategy.