数据仓库相关问题的探讨

综述了数据仓库的概念、特点、结构及其关键技术，对创建数据仓库系统过程中存在的有关问题进行了探讨，并展望了其发展趋势。     

面向企业营销的Web挖掘技术

WWW提供了重要的商业资源,在W eb上进行市场营销数据挖掘是非常有价值的。结合市场营销的发展趋势,探讨W eb挖掘技术及其对制定营销策略的促进作用,通过实验数据说明W eb挖掘将对市场营销提供支持有效决策的参考知识。     

非对称信息下企业信用风险形成机理及其降低策略

信用风险控制既是风险控制研究的理论难点，也是风险控制实践的难点。从非对称信息理论的角度出发。分析非对称信息下信用风险形成的机理，可以得出控制信用风险的关键在于事前阶段的结论。加强客户信用信息管理系统的建设是企业降低信用风险的关键，也是实现企业信用风险标本兼治的第一步。     

面向CRM的数据挖掘应用

近几年来，信息在企业发展中的关键地位得到了越来越多的关注，赢家往往是那些能成功收集、分析、理解信息并根据信息决策的企业，而新型电子商务的关键是它与消费者之间的关系。本文研究了数据挖掘技术在客户关系管理（CRM）中的运用，讨论了企业如何理清和客户之间的关系。     

Environmental protection or subversion in mining? Planning challenges,perspectives and actors at the largest gold deposit in Europe

The gold ores in Roşia Montană have been intensely mined for the last two thousand years, as this mining district was one of the richest gold deposits in the Apuseni Mountains (the so-called Golden Quadrangle of Romania). Itis currently considered the largest gold deposit in Europe. Up until a few decades ago, gold mines had a relatively predictable path, which began with exploration and ended with abandonment. This has since changed, once the impact of abusive past or current exploitation methods and technologies has been deemed unacceptable by the state and the public. With its millennia-old history of mining, Roșia Montană raises the intriguing question of what does the future hold for different actors in a situation that is clearly unsustainable, but which may be continued through environmental rehabilitation, or even a larger mine. We address the question for this particular mine by drawing on a worldwide database of similar cases contained in the Environmental Justice Atlas (EJAtlas). We consider three scenarios, namely: 1) continued degradation with no intervention; 2) approval of large-scale mining, due to international arbitration; 3) environmental rehabilitation. These capture the most plausible future scenarios of the Roșia Montană case and, by relating them to the relevant transnational environmental justice context, we aim at assessing their implications for different actors and also the extent to which they are illustrative for the fate of other mines worldwide. Mine closure and the rehabilitation of the environment, regardless how distant they may seem at the beginning of the prospection and extraction stage, are imminent in the mine life cycle and a mandatory step of the environmental management process. We conclude by suggesting under which governance regimes each scenario is likely to unfold and what implications can be drawn for public policy.     

Reading between the lines: Multidimensional translation in tourism consumption

This paper argues that for translation to enhance the tourist experience literal accuracy is not enough and translations should be culturally sensitive to their target readers. Using the example of museum websites as a form of purposive tourism information designed to both inform and attract potential visitors, this paper analyzes websites of museums in the UK and China. We argue that no matter how accurate a translation may be, if the norms of the target tourist community have been ignored a translation may fail to achieve its purpose and may even have a detrimental effect on the tourism experience. By bringing together translation and tourism theory, we demonstrate when the cultural element of tourism is considered alongside the translation of texts, the need for linguistic accuracy is superseded by a requirement for cultural sensitivity.     

Applying LSA text mining technique in envisioning social impacts of emerging technologies: The case of drone technology

This research proposes a novel method of identifying and understanding the holistic overview of emerging technologies’ unintended consequences. Latent Semantic Analysis (LSA) text mining technique is employed to yield multiple groups of contextually similar terms from future-oriented data sources, comprising both experts’ and the public's concerns regarding future technologies. Resulting term clusters are considered as new abstractions, or so-called scenarios, of future social impacts. Furthermore, the study acquires greater depth and breadth in conceptualizing social impacts through considering condition- and value-related terms as key linking factors to previous social impact-related literature. Our proposed methodology seeks to gain insights into the utilization of future-oriented data sources for the foresight activity, hoping to mitigate public skepticism and pursue a better social acceptance of emerging technologies.     

The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning

Whether investor sentiment affects stock prices is an issue of long-standing interest for economists. We conduct a comprehensive study of the predictability of investor sentiment, which is measured directly by extracting expectations from online user-generated content (UGC) on the stock message board of Eastmoney.com in the Chinese stock market. We consider the influential factors in prediction, including the selections of different text classification algorithms, price forecasting models, time horizons, and information update schemes. Using comparisons of the long short-term memory (LSTM) model, logistic regression, support vector machine, and Naïve Bayes model, the results show that daily investor sentiment contains predictive information only for open prices, while the hourly sentiment has two hours of leading predictability for closing prices. Investors do update their expectations during trading hours. Moreover, our results reveal that advanced models, such as LSTM, can provide more predictive power with investor sentiment only if the inputs of a model contain predictive information.     

Employing structural topic modelling to explore perceived service quality attributes in Airbnb accommodation

This study employs the structural topic model to extract service quality attributes from 242,020 Airbnb reviews in Malaysia. 22 service related topics were extracted from the corpus and four topics have not appeared in previous Airbnb studies. A widely used modified SERVQUAL questionnaire (MSQ) is cross-validated in this study by comparing its service quality attributes with the results of the topic modelling, which indicates that this MSQ can cover general Airbnb service quality attributes. This study also examines the different preferences of Malaysian and international Airbnb users and the changing patterns of the top six service quality attributes during a five-year period. The findings reveal that Malaysian Airbnb users care more about the appearance and location of the property, and international Airbnb users pay more attention to whether the property can accommodate a group of people. In addition, communication with the host is found to play an increasingly important role in Airbnb users’ lodging experiences.     

Visual attention toward tourism photographs with text: An eye-tracking study

This study examines consumers' visual attention toward tourism photographs with text naturally embedded in landscapes and their perceived advertising effectiveness. Eye-tracking is employed to record consumers' visual attention and a questionnaire is administered to acquire information about the perceived advertising effectiveness. The impacts of text elements are examined by two factors: viewers' understanding of the text language (understand vs. not understand), and the number of textual messages (single vs. multiple). Findings indicate that text within the landscapes of tourism photographs draws the majority of viewers' visual attention, irrespective of whether or not participants understand the text language. People spent more time viewing photographs with text in a known language compared to photographs with an unknown language, and more time viewing photographs with a single textual message than those with multiple textual messages. Viewers reported higher perceived advertising effectiveness toward tourism photographs that included text in the known language.