844 resultados para Data mining and knowledge discovery
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Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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This research is looking to find out what benefits employees expect the organization of data governance gains for an organization and how it benefits implementing automated marketing capabilities. Quality and usability of the data are crucial for organizations to meet various business needs. Organizations have more data and technology available what can be utilized for example in automated marketing. Data governance addresses the organization of decision rights and accountabilities for the management of an organization’s data assets. With automated marketing it is meant sending a right message, to a right person, at a right time, automatically. The research is a single case study conducted in Finnish ICT-company. The case company was starting to organize data governance and implementing automated marketing capabilities at the time of the research. Empirical material is interviews of the employees of the case company. Content analysis is used to interpret the interviews in order to find the answers to the research questions. Theoretical framework of the research is derived from the morphology of data governance. Findings of the research indicate that the employees expect the organization of data governance among others to improve customer experience, to improve sales, to provide abilities to identify individual customer’s life-situation, ensure that the handling of the data is according to the regulations and improve operational efficiency. The organization of data governance is expected to solve problems in customer data quality that are currently hindering implementation of automated marketing capabilities.
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This research concerns the Urban Living Idea Contest conducted by Creator Space™ of BASF SE during its 150th anniversary in 2015. The main objectives of the thesis are to provide a comprehensive analysis of the Urban Living Idea Contest (ULIC) and propose a number of improvement suggestions for future years. More than 4,000 data points were collected and analyzed to investigate the functionality of different elements of the contest. Furthermore, a set of improvement suggestions were proposed to BASF SE. Novelty of this thesis lies in the data collection and the original analysis of the contest, which identified its critical elements, as well as the areas that could be improved. The author of this research was a member of the organizing team and involved in the decision making process from the beginning until the end of the ULIC.
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The strongest wish of the customer concerning chemical pulp features is consistent, uniform quality. Variation may be controlled and reduced by using statistical methods. However, studies addressing the application and benefits of statistical methods in forest product sector are scarce. Thus, the customer wish is the root cause of the motivation behind this dissertation. The research problem addressed by this dissertation is that companies in the chemical forest product sector require new knowledge for improving their utilization of statistical methods. To gain this new knowledge, the research problem is studied from five complementary viewpoints – challenges and success factors, organizational learning, problem solving, economic benefit, and statistical methods as management tools. The five research questions generated on the basis of these viewpoints are answered in four research papers, which are case studies based on empirical data collection. This research as a whole complements the literature dealing with the use of statistical methods in the forest products industry. Practical examples of the application of statistical process control, case-based reasoning, the cross-industry standard process for data mining, and performance measurement methods in the context of chemical forest products manufacturing are brought to the public knowledge of the scientific community. The benefit of the application of these methods is estimated or demonstrated. The purpose of this dissertation is to find pragmatic ideas for companies in the chemical forest product sector in order for them to improve their utilization of statistical methods. The main practical implications of this doctoral dissertation can be summarized in four points: 1. It is beneficial to reduce variation in chemical forest product manufacturing processes 2. Statistical tools can be used to reduce this variation 3. Problem-solving in chemical forest product manufacturing processes can be intensified through the use of statistical methods 4. There are certain success factors and challenges that need to be addressed when implementing statistical methods
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A research project submitted to the Faculty of Extension, University of Alberta in partial fulfillment of the requirements for the degree of Master of Arts in Communications and Technology in 2005.
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This study examines the efficiency of search engine advertising strategies employed by firms. The research setting is the online retailing industry, which is characterized by extensive use of Web technologies and high competition for market share and profitability. For Internet retailers, search engines are increasingly serving as an information gateway for many decision-making tasks. In particular, Search engine advertising (SEA) has opened a new marketing channel for retailers to attract new customers and improve their performance. In addition to natural (organic) search marketing strategies, search engine advertisers compete for top advertisement slots provided by search brokers such as Google and Yahoo! through keyword auctions. The rationale being that greater visibility on a search engine during a keyword search will capture customers' interest in a business and its product or service offerings. Search engines account for most online activities today. Compared with the slow growth of traditional marketing channels, online search volumes continue to grow at a steady rate. According to the Search Engine Marketing Professional Organization, spending on search engine marketing by North American firms in 2008 was estimated at $13.5 billion. Despite the significant role SEA plays in Web retailing, scholarly research on the topic is limited. Prior studies in SEA have focused on search engine auction mechanism design. In contrast, research on the business value of SEA has been limited by the lack of empirical data on search advertising practices. Recent advances in search and retail technologies have created datarich environments that enable new research opportunities at the interface of marketing and information technology. This research uses extensive data from Web retailing and Google-based search advertising and evaluates Web retailers' use of resources, search advertising techniques, and other relevant factors that contribute to business performance across different metrics. The methods used include Data Envelopment Analysis (DEA), data mining, and multivariate statistics. This research contributes to empirical research by analyzing several Web retail firms in different industry sectors and product categories. One of the key findings is that the dynamics of sponsored search advertising vary between multi-channel and Web-only retailers. While the key performance metrics for multi-channel retailers include measures such as online sales, conversion rate (CR), c1ick-through-rate (CTR), and impressions, the key performance metrics for Web-only retailers focus on organic and sponsored ad ranks. These results provide a useful contribution to our organizational level understanding of search engine advertising strategies, both for multi-channel and Web-only retailers. These results also contribute to current knowledge in technology-driven marketing strategies and provide managers with a better understanding of sponsored search advertising and its impact on various performance metrics in Web retailing.
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Mobile augmented reality applications are increasingly utilized as a medium for enhancing learning and engagement in history education. Although these digital devices facilitate learning through immersive and appealing experiences, their design should be driven by theories of learning and instruction. We provide an overview of an evidence-based approach to optimize the development of mobile augmented reality applications that teaches students about history. Our research aims to evaluate and model the impacts of design parameters towards learning and engagement. The research program is interdisciplinary in that we apply techniques derived from design-based experiments and educational data mining. We outline the methodological and analytical techniques as well as discuss the implications of the anticipated findings.
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Triple quadrupole mass spectrometers coupled with high performance liquid chromatography are workhorses in quantitative bioanalyses. It provides substantial benefits including reproducibility, sensitivity and selectivity for trace analysis. Selected Reaction Monitoring allows targeted assay development but data sets generated contain very limited information. Data mining and analysis of non-targeted high-resolution mass spectrometry profiles of biological samples offer the opportunity to perform more exhaustive assessments, including quantitative and qualitative analysis. The objectives of this study was to test method precision and accuracy, statistically compare bupivacaine drug concentration in real study samples and verify if high resolution and accurate mass data collected in scan mode can actually permit retrospective data analysis, more specifically, extract metabolite related information. The precision and accuracy data presented using both instruments provided equivalent results. Overall, the accuracy was ranging from 106.2 to 113.2% and the precision observed was from 1.0 to 3.7%. Statistical comparisons using a linear regression between both methods reveal a coefficient of determination (R2) of 0.9996 and a slope of 1.02 demonstrating a very strong correlation between both methods. Individual sample comparison showed differences from -4.5% to 1.6% well within the accepted analytical error. Moreover, post acquisition extracted ion chromatograms at m/z 233.1648 ± 5 ppm (M-56) and m/z 305.2224 ± 5 ppm (M+16) revealed the presence of desbutyl-bupivacaine and three distinct hydroxylated bupivacaine metabolites. Post acquisition analysis allowed us to produce semiquantitative evaluations of the concentration-time profiles for bupicavaine metabolites.
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Remote Data acquisition and analysing systems developed for fisheries and related environmental studies have been reported. It consists of three units. The first one namely multichannel remote data acquisition system is installed at the remote place powered by a rechargeable battery. It acquires and stores the 16 channel environmental data on a battery backed up RAM. The second unit called the Field data analyser is used for insitue display and analysis of the data stored in the backed up RAM. The third unit namely Laboratory data analyser is an IBM compatible PC based unit for detailed analysis and interpretation of the data after bringing the RAM unit to the laboratory. The data collected using the system has been analysed and presented in the form of a graph. The system timer operated at negligibly low current, switches on the power to the entire remote operated system at prefixed time interval of 2 hours.Data storage at remote site on low power battery backedupRAM and retrieval and analysis of data using PC are the special i ty of the system. The remote operated system takes about 7 seconds including the 5 second stabilization time to acquire and store data and is very ideal for remote operation on rechargeable bat tery. The system can store 16 channel data scanned at 2 hour interval for 10 days on 2K backed up RAM with memory expansion facility for 8K RAM.