Text mining approach to explore dimensions of airline customer satisfaction using online customer reviews

The airline industry operates in a highly competitive market, in which achieving and maintaining a high level of passenger satisfaction is seen as a key competitive advantage. This study presents a novel framework for measuring customer satisfaction in the airline industry. Using text mining methods we explore Online Customer Reviews (OCRs) to provide guidelines for airlines companies to improve in competitiveness. We analyze a database of more than 55,000 OCRs, covering over 400 airlines and passengers from 170 countries. Using a Latent Dirichlet Allocation model we identified 27 dimensions of satisfaction described by 882 adjectives. Dimensions and adjectives were used to predict airline recommendation by customers, resulting in an accuracy of 79.95%. The most relevant dimensions for airlines' recommendation prediction were calculated. OCRs were stratified according to several variables. Of those, type of passenger impacted the least on the number of dimensions of customer satisfaction, while type of cabin flown impacted the most. Observing results in different publication years we showed airline customer trends through time. Our method showed sensitiveness to identify variations in dimensions distribution according to different passenger characteristics and preferences. Practical implications are that airline service providers aiming at maximizing customer satisfaction should focus their efforts on (i) customer service to first class passengers, (ii) comfort to premium economy passengers, and (iii) checking luggage and waiting time to economy class travelers. Regression analysis revealed cabin staff, onboard service and value for money as top three dimensions of satisfaction to predict the recommendation of airlines. Designing services that excel in those dimensions is likely to improve the company's performance with customers.     

Literature-related discovery (LRD): Potential treatments for cataracts

Literature-related discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e., potential discovery). The open discovery systems (ODS) component of LRD starts with a problem to be solved, and generates solutions to that problem through potential discovery. We have been using ODS LRD to identify potential treatments or preventative actions for challenging medical problems, among myriad other applications.This paper describes the second medical problem we addressed (cataract) using ODS LRD; the first problem addressed was Raynaud's Phenomenon (RP), and was described in the third paper of this Special Issue. Cataract was selected because it is ubiquitous globally, appears intractable to all forms of treatment other than surgical removal of cataracts, and is a major cause of blindness in many developing countries.The ODS LRD study had three objectives: a) identify non-drug non-surgical treatments that would 1) help prevent cataracts, or 2) reduce the progression rate of cataracts, or 3) stop the progression of cataracts, or 4) maybe even reverse the progression of cataracts; b) demonstrate that we could solve an ODS LRD problem with no prior knowledge of any results or prior work (unlike the case with the RP problem); c) determine whether large time savings in the discovery process were possible relative to the time required for conducting the RP study. To that end, we used the MeSH taxonomy of MEDLINE to restrict potential discoveries to selected semantic classes, as a substitute for the manually-intensive process used in the RP study to restrict potential discoveries to selected semantic classes. We also used additional semantic filtering to identify potential discovery within the selected semantic classes.All these goals were achieved. As will be shown, we generated large amounts of potential discovery in more than an order of magnitude less time than required for the RP study. We identified many non-drug non-surgical treatments that may be able to reduce or even stop the progression rate of cataracts. Time, and much testing, will determine whether this is possible. Finally, the methodology has been developed to the point where ODS LRD problems can be solved with no results or knowledge of any prior work.     

Literature-Related Discovery (LRD): Potential treatments for Parkinson's Disease

Literature-Related Discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e., potential discovery). The open discovery systems (ODS) component of LRD starts with a problem to be solved, and generates solutions to that problem through potential discovery. We have been using ODS LRD to identify potential treatments or preventative actions for challenging medical problems, among myriad other applications. The previous two papers in this Special Issue describe the application of ODS LRD to Raynaud's Phenomenon (RP) and to cataracts.Parkinson's Disease (PD) is a progressive neurodegenerative disorder, affecting approximately 1% of individuals older than 60 years, and is characterized by resting tremor, rigidity, bradykinesia, and postural instability. We selected the subject of PD because of its global prevalence, and its apparent intractability to all treatments except for palliative remediation mainly through drugs or surgery.Our first goal was to identify non-drug non-surgical treatments that would 1) prevent the occurrence, or 2) reduce the progression rate, or 3) stop the progression, or 4) maybe even reverse the progression, of PD. Our second goal was to demonstrate that we could again solve an ODS problem (using LRD) with no prior knowledge of any results or prior work (unlike the case of the RP problem). As in the ‘cataract’ example, we used the MeSH taxonomy of MEDLINE to restrict potential discoveries to selected semantic classes, and to identify potential discoveries efficiently. Our third goal was to generate large amounts of potential discovery in more than an order of magnitude less time than required for the RP study. The discovery generation methodology has been developed to the point where ODS LRD problems can be solved with no results or knowledge of any prior work.     

Literature-related discovery (LRD): Water purification

Literature-related discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e., potential discovery). LRD has two main components that differ in their methodological approach to discovery: Literature-based discovery (LBD) produces potential discovery through analysis of the technical literature alone; Literature-assisted discovery (LAD) produces potential discovery through both analysis of the technical literature and use of selected authors of that literature. These authors generate potential discovery as proposers, workshop/panel participants, or in other active roles.The open discovery systems (ODS) component of LRD starts with a problem to be solved, and generates solutions to that problem through potential discovery. We have been using ODS LRD to identify potential treatments or preventative actions for challenging medical problems, among myriad other applications. The previous four papers in this Special Issue describe the application of ODS LRD (specifically, the ODS LBD variant) to Raynaud's Phenomenon (RP), cataracts, Parkinson's Disease (PD), and Multiple Sclerosis (MS).One goal of the present study was to determine whether LRD could be successfully applied (for the first time) to a challenging non-medical technical problem to generate potential discovery. The second goal was to explore the use of both LRD variants (LBD and LAD) to a non-medical technical problem. We selected the problem of water purification (WP) because of universal applicability and sponsor interest.We used LRD to identify purification concepts, technology components and systems that could lead to improved water purification techniques. We accessed many disparate disciplines to identify purification concepts from literatures not normally associated with water purification. We used two LBD approaches, Cluster Filtering and Latent Semantic Indexing (LSI), to search for potential discovery. We generated voluminous amounts of potential discovery, and believe we have only scratched the surface of what is possible. We also ran a short experiment using LAD to identify experts associated with potential discovery concepts, and use their expertise to generate potential discovery for water purification.     

数据挖掘的商务应用前景

数据挖掘已经成为许多商业领域的一个热门话题。数据挖掘已经成为许多企业在国际市场上赢 得竞争优势的重要的竞争工具之一。国内外早期的研究集中在算法的研究上。其实很多时候技术不是主要 的问题。如何实现从技术到商业的应用才是困扰业界的主要难题。本文试图在这方面有所贡献。本文试图 分别从实践和理论两个角度来阐释数据挖掘的现实的实用性和战略的重要性。本文以一个零售行业的数据 挖掘案例探讨了数据挖掘的商务应用;从技术和商业需求两个方面分别研究了数据挖掘商务应用的可行 性,并指出因竞争战略的细化导致了对数据挖掘的商业需求;最后根据实践经验讨论了数据挖掘在几个典型 行业的应用,希望能拓展我们对数据挖掘的理论和实践的认识。     

The commodity super price cycle and real options: Implications for the Greeks of mining firms

The Real Options Approach (ROA) to the management and valuation of mining firms should impart a distinctive pattern to the time path of the Greeks displayed by such firms during the recent price super cycle. This paper simulates the delta, gamma, vega and rho of a gold mining firm holding a portfolio of heterogeneous mines over the recent gold price cycle, to find out the telltale signs that the ROA should leave on the trajectories exhibited by such variables during that period. We show that the ROA and the standard NPV approach to mine management and valuation predict markedly different trajectories for the Greeks.     

Oracle全文检索技术的应用

随着现代通信技术以及网络技术的发展,人们在工作中需要面对的信息量越来越大,处理海量信息已经成为人们工作中的最大难题。本文介绍了Oracle Text的关键技术和运行原理,并采用该技术将基于Oracle数据库的文章进行信息检索。通过研究了Oracle在全文检索方面的组件Oracle Text的体系结构,Oracle Text应用步骤及它的实现,应用Oracle Text组件来实现基于Oracle数据库的全文检索,达到解决海量信息的全文检索目的。     

徐州矿务集团信息化管控统一平台建设探讨及设计

根据煤矿信息化建设存在的问题,阐述了矿务集团信息化管控统一平台建设的必要性,并分析了其具体实现的关键性工作,最后给出矿务集团信息化管控统一平台建设的概要设计。     

淄矿集团构建本质安全管理体系的探索与实践

为了减少煤矿安全事故的发生,建设本质安全型矿井是煤炭工业发展的必然趋势。结合本质安全管理体系的建设情况,从理念引导、管理创新、科技推进、员工培训等方面介绍了本质安全管理体系的建设与实施情况。