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Knowledge discovery from a more than a decade studies on healthcare Big Data systems: a scientometrics study

finding shows the “Meta-analysis and evidence” is the most used methodology in published papers. We applied data mining techniques for predicting using methodologies in the various databases to achieving ... methodology Based on descriptive statistics, “Meta-analysis and evidence” is a methodology used in most papers, but this research is based on the knowledge discovery, applied data mining techniques to

Looking for exceptions on knowledge rules induced from HIV cleavage data set

The aim of data mining is to find useful knowledge inout of databases. In order to extract such knowledge, several methods can be used, among them machine learning (ML) algorithms. In this work we ... , high volumes of data have been produced. The sequencing of the human genome and that of other organisms is just one element of an emerging trend in the life sciences. While the knowledge, experience, and

Biological Knowledge Discovery and Data Mining

datadriven, where knowledge discovery and data mining (KDD) processes are playing increasingly important roles. While tremendous progress has been made over the years, many of the fundamental problems in ... genetics data-rich. The ongoing influx of these data, the inherent uncertainties in data collection processes, and the gap between data collection and knowledge curation have created exciting opportunities

Producing knowledge by admitting ignorance: Enhancing data quality through an “I don’t know” option in citizen science

The “noisy labeler problem” in crowdsourced data has attracted great attention in recent years, with important ramifications in citizen science, where non-experts must produce high-quality data ... Knowledge discovery and data mining-KDD 08 . New York, New York, USA: ACM Press; 2008 . p. 614 . 29. Li Q , Ma F , Gao J , Su L , Quinn CJ . Crowdsourcing high quality labels with a tight budget . Proceedings

Big Data and discrimination: perils, promises and solutions. A systematic review

order to (1) understand the causes and consequences of discrimination in data mining, (2) identify barriers to fair data-mining and (3) explore potential solutions to this problem.MethodsSix databases ... building proper models, such as the creation of a knowledge base platform for fairness in data mining that could be investigated by data scientists in case they stumbled upon problematic correlations; and (d

Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a survey

also provides an overview of massive parallelism support that is capable of scaling computation effectively and efficiently in the era of Big Data. ... (DM) is the core stage of the knowledge discovery process that aims to extract interesting and potentially useful information from data (Goodfellow et al. 2016; Mierswa 2017). Although during this work

Biodiversity Observations Miner: A web application to unlock primary biodiversity data from published literature

Here, we present a novel, open source text mining tool, the Biodiversity Observations Miner (BOM). This web application, written in R, allows the semi-automated discovery of punctual biodiversity ... data discovery tasks in large quantities of documents. However, text mining approaches for knowledge discovery and retrieval have been limited in biodiversity science compared to other disciplines. New

Data mining combined to the multicriteria decision analysis for the improvement of road safety: case of France

hybrid approach based on data mining techniques combined to the multicriteria decision methods. This approach allows to extract the most relevant association rules. The results thus obtained can be easily ... DGPN General Directorate of the National Police DM data mining ELECTRE ELimination and Choice Translating Reality GDP gross domestic product IDE integrate development environment KDD knowledge discovery


knowledge. Anthropological research on mining and its effects on indigenous peoples and local communities has been a topic of classic ethnographies, like June Nash's We eat the mines and the mines eat us ... specificities of mining in Brazil and the research that has been carried out by Anthropologists in interaction with researchers from different areas of knowledge, including sociology, geography, engineering

Evaluación del desempeño de roles en el proceso de formación del Ingeniero Informático

future behaviors, and discover hidden relationships between data and new knowledge. This is why the application of data mining is proposed. ... , Craig; BRIN, Sergey; MOTWANI, Rajeev. Beyond market baskets: Generalizing association rules to dependence rules. Data mining and knowledge discovery, 1998, vol. 2, no 1, p. 39-68. UNIVERSIDAD DE

Editorial Message: Special Issue on Fuzzy System in Data Mining and Knowledge Discovery: Modelling and Application

in Data mining and Knowledge discovery: Modelling and application, we would like to publish the latest, innovative, and outstanding research results in the International Journal of Fuzzy Systems (IJFS ... ). Fuzzy system in data mining and knowledge discovery is an interdisciplinary area focusing upon methodologies for extracting useful knowledge from data. Data mining and knowledge discovery has studied

STEM Pedagogical Content Knowledge Scale (STEMPCK): A Validity and Reliability Study

The aim of this study was to develop the STEM Pedagogical Content Knowledge Scale (STEMPCK Scale). Exploratory and confirmatory factor analyses were conducted to examine the structural validity of ... , & Wiebe, 2015; Viiri, 2003; Y?ld?r?m & Selvi, 2015, Yusof et al., 2012) . Stage 3. The knowledge gained from the literature and the data gathered from interviews were used to develop a draft scale that

Multiple changepoint detection in categorical data streams

prior knowledge of the stream. This paper introduces such a method, which can accurately detect changepoints in categorical data streams with fixed storage and computational requirements. The detector ... ) Cao, F., Huang, J.Z.: A concept-drifting detection algorithm for categorical evolving data. In: Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 485–496. Springer, Berlin (2013)Google

Postgraduates Producing Knowledge

process of their publication reveals important features of the production, authentication, and circulation of knowledge in the academic study of religion and religions. ... provides background. The articles in this issue arose out of an ongoing experiment in knowledge production in a postgraduate course on theory and method in the study ofreligion in the Department of Religious

CBSSD: community-based semantic subgroup discovery

introduces the relevant concepts and presents the related work in the fields of complex networks, knowledge graphs and ontologies, enrichment analysis, semantic data mining, semantic subgroup discovery and ... background knowledge in data analysis is referred to as semantic data mining. A specific semantic data mining task is semantic subgroup discovery: a rule learning approach enabling ontology terms to be used in

Effects of office space and colour on knowledge sharing and work stress

With the aid of empirical research, this study aims to verify the effects of the variables Office Space and Colour on Knowledge Sharing and Work Stress. Taking the domestic technology industry as the ... , 347 valid copies were retrieved. Reliability analysis, factor analysis and hierarchical regression were used to analyse the data. The research outcomes show the significant effects of Office Space and

The convergence computing model for big sensor data mining and knowledge discovery

model of cloud computing and cloud storage today is the basis for the accumulation of the results of data mining and knowledge discovery. Means of communication and remote access can solve the problem of ... . Convergence computing; Wireless sensor network; Fog computing; GRID; Cloud computing; Cloud storage; Mobile computing; Data mining; Knowledge discovery - Sensor data is one of the big data, and its

EACD: evolutionary adaptation to concept drifts in data streams

time. The evolution of data streams can be viewed as a problem of changing environment, and evolutionary algorithms offer a natural solution to this problem. The method proposed in this paper uses random ... SIGKDD international conference on Knowledge discovery and data mining, pp 139–148. ACMGoogle Scholar Bifet A, Holmes G, Kirkby R, Pfahringer B (2010a) Moa: massive online analysis. J Mach Learn Res 11

Aviation Data Mining

We explore different methods of data mining in the field of aviation and their effectiveness. The field of aviation is always searching for new ways to improve safety. However, due to the large ... and aviation safety case study . In Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining , pages 47 { 56 . ACM, 2010 . [3] J. W. Hunt and T. G. Szymanski

Using Existing Data to Advance Knowledge About Adolescent and Emerging Adult Marijuana Use in the Context of Changes in Marijuana Policies

examples of trend and quasi-experimental studies to highlight the unique strengths of each. We also identify gaps in existing knowledge and offer recommendations for future data collection and research that ... uses these data sources. National Survey on Drug Use and Health (NSDUH) The National Survey on Drug Use and Health (NSDUH) is an initiative of the Substance Abuse and Mental Health Services