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Evolution von Relationen in temporalen partiten Themen-Graphen

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ISBN: 9783731503408 Year: Pages: II, 136 p. DOI: 10.5445/KSP/1000045521 Language: GERMAN
Publisher: KIT Scientific Publishing
Subject: Business and Management
Added to DOAB on : 2019-07-30 20:02:00
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In this work a model is engineered to depict topic relationships as graphs between detected topics of different time windows. By varying and shifting the time span of consideration the relationships between topics can be mapped with a variable complexity including the topic frequencies. Topic life cycles as well as changes in thematic relationships and their evolution become perceptible. Topics found can be matched in structure as well as their temporal progression to existing events.

Neuroanatomy for the XXIst Century

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889199167 Year: Pages: 199 DOI: 10.3389/978-2-88919-916-7 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Neurology
Added to DOAB on : 2016-01-19 14:05:46
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An explosion of new techniques with vastly improved visualization and sensitivity is leading a veritable revolution in modern neuroanatomy. Basic questions related to cell types, input localization, and connectivity are being re-visited and tackled with significantly more accurate and higher resolution experimental approaches. A major goal of this e-Book is thus to highlight in one place the impressive range of available techniques, even as these are fast becoming routine. This is not meant as a technical review, however, but rather will project the technical explosion as indicative of a field now in a vibrant state of renewal. Thus, contributions will be mainly research articles using the newer techniques. A second goal is to showcase what has become the conspicuous interdisciplinary reach of the field: neuroanatomical standards and the close association of structure-function and underlying circuitry mechanisms are increasingly relevant to investigations in development, physiology, and disease. Another feature of this Research Topic is that it includes a breadth of cross-species contributions from investigators working with rodent, nonhuman primate, and human brains. This is important since most of our current knowledge of brain structure has been obtained from experimental animals. However, recent technical advances, coupled with researcher willingness to use the human tissue available, will undoubtedly lead to major advances in the near future regarding human brain mapping and connectomes. Thus, of particular interest will be the methods that can help to define general wiring principles in the brain, both structural and functional. Overall, the state of the field is: exciting.

Clinical Text Mining: Secondary Use of Electronic Patient Records

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ISBN: 9783319785028 9783319785035 Year: Pages: 181 DOI: https://doi.org/10.1007/978-3-319-78503-5 Language: English
Publisher: Springer Nature Grant: Riksbankens Jubileumsfond; Stockholm University
Subject: Medical technology
Added to DOAB on : 2018-06-22 15:52:54
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This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records.It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The difference between rule-based and machine learning-based methods, as well as between supervised and unsupervised machine learning methods, are also explained. Next, ethical concerns regarding the use of sensitive patient records for research purposes are discussed, including methods for de-identifying electronic patient records and safely storing patient records. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters.The book provides a comprehensive overview of technical issues arising in clinical text mining, and offers a valuable guide for advanced students in health informatics, computational linguistics, and information retrieval, and for researchers entering these fields.

Computational Systems Biology of Pathogen-Host Interactions

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889198214 Year: Pages: 198 DOI: 10.3389/978-2-88919-821-4 Language: English
Publisher: Frontiers Media SA
Subject: Microbiology --- Science (General)
Added to DOAB on : 2016-01-19 14:05:46
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A thorough understanding of pathogenic microorganisms and their interactions with host organisms is crucial to prevent infectious threats due to the fact that Pathogen-Host Interactions (PHIs) have critical roles in initiating and sustaining infections. Therefore, the analysis of infection mechanisms through PHIs is indispensable to identify diagnostic biomarkers and next-generation drug targets and then to develop strategic novel solutions against drug-resistance and for personalized therapy. Traditional approaches are limited in capturing mechanisms of infection since they investigate hosts or pathogens individually. On the other hand, the systems biology approach focuses on the whole PHI system, and is more promising in capturing infection mechanisms. Here, we bring together studies on the below listed sections to present the current picture of the research on Computational Systems Biology of Pathogen-Host Interactions:- Computational Inference of PHI Networks using Omics Data- Computational Prediction of PHIs- Text Mining of PHI Data from the Literature- Mathematical Modeling and Bioinformatic Analysis of PHIs Computational Inference of PHI Networks using Omics Data Gene regulatory, metabolic and protein-protein networks of PHI systems are crucial for a thorough understanding of infection mechanisms. Great advances in molecular biology and biotechnology have allowed the production of related omics data experimentally. Many computational methods are emerging to infer molecular interaction networks of PHI systems from the corresponding omics data. Computational Prediction of PHIs Due to the lack of experimentally-found PHI data, many computational methods have been developed for the prediction of pathogen-host protein-protein interactions. Despite being emerging, currently available experimental PHI data are far from complete for a systems view of infection mechanisms through PHIs. Therefore, computational methods are the main tools to predict new PHIs. To this end, the development of new computational methods is of great interest. Text Mining of PHI Data from Literature Despite the recent development of many PHI-specific databases, most data relevant to PHIs are still buried in the biomedical literature, which demands for the use of text mining techniques to unravel PHIs hidden in the literature. Only some rare efforts have been performed to achieve this aim. Therefore, the development of novel text mining methods specific for PHI data retrieval is of key importance for efficient use of the available literature. Mathematical Modeling and Bioinformatic Analysis of PHIs After the reconstruction of PHI networks experimentally and/or computationally, their mathematical modeling and detailed computational analysis is required using bioinformatics tools to get insights on infection mechanisms. Bioinformatics methods are increasingly applied to analyze the increasing amount of experimentally-found and computationally-predicted PHI data. Acknowledgements: We, editors of this e-book, acknowledge Emrah Nikerel (Yeditepe University, Turkey) and Arzucan Özgür (Bogaaziçi University, Turkey) for their contributions during the initiation of the Research Topic.

Sentiment Analysis for Social Media

Authors: ---
ISBN: 9783039285723 / 9783039285730 Year: Pages: 152 DOI: 10.3390/books978-3-03928-573-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-06-09 16:38:56
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Sentiment analysis is a branch of natural language processing concerned with the study of the intensity of the emotions expressed in a piece of text. The automated analysis of the multitude of messages delivered through social media is one of the hottest research fields, both in academy and in industry, due to its extremely high potential applicability in many different domains. This Special Issue describes both technological contributions to the field, mostly based on deep learning techniques, and specific applications in areas like health insurance, gender classification, recommender systems, and cyber aggression detection.

Human and Animal Sensitivity: How Stock-People and Consumer Perception Can Affect Animal Welfare

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ISBN: 9783039212613 9783039212620 Year: Pages: 234 DOI: 10.3390/books978-3-03921-262-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Animal Sciences
Added to DOAB on : 2019-12-09 11:49:15
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This book presents cross-discipline studies covering aspects ranging from animal science to social/consumer sciences and psychology, with the aim to collect and disseminate information promoting the continuous enhancement of animal welfare by improving stakeholders’ perception of animal welfare. Although animal welfare is about how the animals perceive the surrounding environment, the actual welfare of the animals is dependent on how the stakeholders perceive and weigh animal welfare. The stakeholders can, either directly (i.e., through stock-people interaction with the animals) or indirectly (e.g., when retailers and consumers are willing to pay more for high welfare animal-based products), affect the way animals are kept and handled.

Keywords

veterinary student --- animal ethics --- pain perception --- animal --- animal welfare --- Animal welfare --- husbandry practices --- lambs --- pain --- sheep farmers --- perception --- agreement --- aggression --- animal welfare --- desensitization --- perception --- pigs --- animal welfare --- young adult --- animal attitudes --- children --- farm animals --- animal welfare --- education --- technology --- animal welfare --- Asia --- knowledge --- slaughter --- transport --- training --- animal welfare --- benefit --- profit --- human health --- Asia --- livestock --- farmer perception --- citizen perception --- qualitative research --- free elicitation narrative interviews --- animal welfare --- consumer --- willingness to pay --- pig --- castration --- immunocastration --- information --- survey --- human-animal relationship --- fear --- laying hen --- stockpeople attitudes --- stockperson behaviour --- egg farm --- albumen corticosterone --- welfare --- animal welfare --- stakeholder perception --- text mining --- horse --- donkey --- goat --- sheep --- turkey --- farm animal welfare (FAW) --- willingness to pay --- food safety concerns --- ethical concerns --- perceived consumer effectiveness --- broiler --- dairy buffalo --- human-animal relationship --- animal behavior --- test-retest reliability --- avoidance distance --- milk production --- animal welfare --- animal welfare --- stunning --- religious slaughter --- veterinary students --- Halal meat --- racehorse welfare --- staff shortages --- horse–human relationship --- standards of care --- employee relations --- consumer demand --- economics --- farm animal welfare --- producer perspective

Formal and Methodological Approaches to Applied Linguistics

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ISBN: 9783039283224 9783039283231 Year: Pages: 144 DOI: 10.3390/books978-3-03928-323-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Linguistics
Added to DOAB on : 2020-04-07 23:07:08
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The goal of this Special Issue is to bring together state-of-the art articles on applied linguistics which reflect investigation carried out by researchers from different parts of the world. By bringing together papers from different perspectives, we hope to be able to gain a better understanding of the field. Hence, this Special Issue intends to address the study of language in its different dimensions and within the framework of multiple methodologies and formal accounts as used by researchers in the field. This Special Issue is dedicated to research in any area related to applied linguistics, including language acquisition and language learning; language teaching and curriculum design; language for specific purposes; psychology of language, child language and psycholinguistics; sociolinguistics; pragmatics; discourse analysis; corpus linguistics, computational linguistics and language engineering; lexicology and lexicography; and translation and interpretation.

Keywords

linguistic landscape --- minority language --- bilingualism --- multilingualism --- language contact --- bilingualism --- language contact --- pattern borrowing --- Russian --- Samoyedic languages --- Tungusic languages --- reflexive --- valency changing --- middle voice --- English for Specific Purposes --- Content and Language Integrated Learning (CLIL) --- business English --- legal English --- teacher training --- foreign language teaching --- Integrating Content and Language in Higher Education (ICLHE) --- English as a medium of instruction (EMI) --- teaching methodologies in Higher Education --- internationalization of the curriculum --- named river --- conceptual information extraction --- geographic contextualization --- text mining --- Frame-Based Terminology --- food --- idiom --- metaphor --- metonymy --- English as a Foreign Language --- lexemic transfer --- lemmatic transfer --- Lexical Crosslinguistic Influence --- Study Abroad --- language policy --- higher education --- internationalisation --- discourse analysis --- language diversity --- language attitudes --- English linguistic imperialism --- Spanish universities --- modals --- late Modern English scientific writing --- Coruña Corpus --- spontaneous translanguaging --- discourse practices --- language acquisition --- translation --- corpus analysis --- domain loss --- frame-based terminology --- conceptual complexes --- grammatical gender --- interference --- cognates --- Papiamentu --- Spanish --- n/a

Big Data Research for Social Sciences and Social Impact

Authors: --- ---
ISBN: 9783039282203 9783039282210 Year: Pages: 416 DOI: 10.3390/books978-3-03928-221-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-04-07 23:07:09
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A new era of innovation is enabled by the integration of social sciences and information systems research. In this context, the adoption of Big Data and analytics technology brings new insight to the social sciences. It also delivers new, flexible responses to crucial social problems and challenges. We are proud to deliver this edited volume on the social impact of big data research. It is one of the first initiatives worldwide analyzing of the impact of this kind of research on individuals and social issues. The organization of the relevant debate is arranged around three pillars: Section A: Big Data Research for Social Impact: • Big Data and Their Social Impact; • (Smart) Citizens from Data Providers to Decision-Makers; • Towards Sustainable Development of Online Communities; • Sentiment from Online Social Networks; • Big Data for Innovation. Section B. Techniques and Methods for Big Data driven research for Social Sciences and Social Impact: • Opinion Mining on Social Media; • Sentiment Analysis of User Preferences; • Sustainable Urban Communities; • Gender Based Check-In Behavior by Using Social Media Big Data; • Web Data-Mining Techniques; • Semantic Network Analysis of Legacy News Media Perception. Section C. Big Data Research Strategies: • Skill Needs for Early Career Researchers—A Text Mining Approach; • Pattern Recognition through Bibliometric Analysis; • Assessing an Organization’s Readiness to Adopt Big Data; • Machine Learning for Predicting Performance; • Analyzing Online Reviews Using Text Mining; • Context–Problem Network and Quantitative Method of Patent Analysis. Complementary social and technological factors including: • Big Social Networks on Sustainable Economic Development; Business Intelligence.

Keywords

big data --- illegal accommodation --- institutional innovation --- transaction costs --- housing problem --- building stock management --- Hong Kong --- information diffusion --- community detection --- topic analysis --- sentiment analysis --- social networks --- Social network --- sustainable development --- review voting --- online community --- paradox --- smart citizens --- experimental cities --- smart cities --- technopolitics --- big data --- Barcelona --- data commons --- decision-makers --- policy --- GDPR --- big data --- social sciences --- decision-making --- data analyst --- filtering --- framing --- big data --- maturity model --- temporal analytics --- advanced business analytics --- big data analytic methods --- semantic network analysis --- framings --- NodeXL --- promising technology --- research frontier --- bibliometric analysis --- hype cycle --- technology platforms --- sustainable agri-food systems --- innovation in sustainable agriculture --- online data --- data mining --- TP organics --- big data research --- point of interests (POI) --- sustainability development --- spatial accessibility of residential public services --- Xiamen City --- big data --- sales prediction --- online word-of-mouth --- dynamic topic model --- product attributes --- back-propagation neural network --- systematic and replicable patent analysis method --- problem-solved concept --- context–problem network --- network data analysis --- sustainable wireless energy transmission technology --- big data analytics --- text mining --- association rule --- car review --- skills --- researchers --- early career --- text mining --- social media big data --- lbsn --- check-in density --- spatiotemporal analysis --- KDE --- GWR --- SDE --- Guangzhou --- educational data mining --- learning analytics --- machine learning --- big data --- prediction grades --- destination image --- user-generated content --- online travel review --- big data analytics --- opinion mining --- sentiment analysis --- resource optimisation --- place sustainability --- TripAdvisor --- Greek Attica --- opinion mining --- social media --- social networks --- sentiment analysis --- sentiment polarity classification --- social impact --- big data research --- information systems --- analytics --- decision making --- social sciences --- big data research --- social and humanistic computing --- social sciences --- social good --- social impact --- machine learning --- knowledge management --- web science --- data science --- social inclusive economic growth --- sustainability --- innovation --- innovation networks

Empirical Finance

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ISBN: 9783038977063 Year: Pages: 276 DOI: 10.3390/books978-3-03897-707-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Economics
Added to DOAB on : 2019-04-05 10:34:31
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There is no denying the role of empirical research in finance and the remarkable progress of empirical techniques in this research field. This Special Issue focuses on the broad topic of “Empirical Finance” and includes novel empirical research associated with financial data. One example includes the application of novel empirical techniques, such as machine learning, data mining, wavelet transform, copula analysis, and TV-VAR, to financial data. The Special Issue includes contributions on empirical finance, such as algorithmic trading, market efficiency, market microstructure, portfolio theory and asset allocation, asset pricing models, liquidity risk premium, currency crisis, return predictability, and volatility modeling.

Keywords

text similarity --- text mining --- machine learning --- SVM --- neural network --- LSTM --- credit risk --- ensemble learning --- deep learning --- bagging --- random forest --- boosting --- deep neural network --- causality-in-variance --- cross-correlation function --- housing and stock markets --- algorithmic trading --- take profit --- stop loss --- MACD --- ATR --- city banks --- dependence structure --- copula --- n/a --- market microstructure --- price discovery --- latency --- currency crisis --- random forests --- wavelet transform --- predictive accuracy --- housing price --- bank credit --- housing loans --- real estate development loans --- TVP-VAR model --- exchange rate --- volatility --- exports --- ARDL --- Vietnam --- crude oil futures prices forecasting --- convolutional neural networks --- short-term forecasting --- utility of international currency --- inertia --- liquidity risk premium --- US dollar --- Japanese yen --- cointegration --- statistical arbitrage --- natural gas --- wholesale electricity --- futures market --- spark spread --- earnings management --- earnings manipulation --- earnings quality --- initial public offering --- IPO --- asset pricing model --- data mining --- bankruptcy prediction --- financial and non-financial variables --- institutional investors’ shareholdings --- panel data model --- piecewise regression model --- global financial crisis --- gold return --- asymmetric dependence --- financial market stress --- robust regression --- quantile regression --- structural break --- flight to quality

Knowledge Manageation and Big Data: Implications for Sustainability, Policy Making and Competitiveness

Authors: ---
ISBN: 9783039280087 9783039280094 Year: Pages: 416 DOI: 10.3390/books978-3-03928-009-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Social Sciences --- Education
Added to DOAB on : 2020-01-07 09:21:22
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The evolution of knowledge management theory and the special emphasis on human and social capital sets new challenges for knowledge-driven and technology-enabled innovation. Emerging technologies including big data and analytics have significant implications for sustainability, policy making, and competitiveness. This edited volume promotes scientific research into the potential contributions knowledge management can make to the new era of innovation and social inclusive economic growth. We are grateful to all the contributors of this edition for their intellectual work. The organization of the relevant debate is aligned around three pillars: SECTION A. DATA, KNOWLEDGE, HUMAN AND SOCIAL CAPITAL FOR INNOVATION: We elaborate on the new era of knowledge types and the emerging forms of social capital and their impact on technology-driven innovation. Topics include: Social Networks; Smart Education; Social Capital; Corporate Innovation; Disruptive Innovation; Knowledge integration; Enhanced Decision-Making. SECTION B. KNOWLEDGE MANAGEMENT & BIG DATA ENABLED INNOVATION: In this section, knowledge management and big data applications and systems are presented. Selective topic include: Crowdsourcing Analysis; Natural Language Processing; Data Governance; Knowledge Extraction; Ontology Design Semantic Modeling SECTION C. SUSTAINABLE DEVELOPMENT: In the section, the debate on the impact of knowledge management and big data research to sustainability is promoted with integrative discussion of complementary social and technological factors including: Big Social Networks on Sustainable Economic Development; Business Intelligence

Keywords

innovation capability --- social capital --- knowledge creation --- human capital investment --- training --- education --- communication --- six sigma --- structural equation model --- leadership --- innovation performance --- knowledge sharing --- social capital --- project-based organization --- citizen-scientist --- climate change --- crowdsourcing --- MTurk --- social networks --- Twitter --- social networks --- big data --- big data analysis --- sustainable development --- text mining --- NLP --- technological information --- patent analysis --- text structure --- top management team --- strategic decision-making --- risk perception --- knowledge creation process --- process innovation capability --- product innovation capability --- sustainable competitive advantage --- data governance --- cloud computing --- cloud data governance --- taxonomy --- systematic review --- holistic --- text feature extraction --- patent analysis --- hybrid neural networks --- mechanical patent classification --- international technological collaboration --- IC manufacturing --- patent association analysis --- social network analysis --- collaboration network --- corporate sustainability --- business intelligence --- multi-dimensional data model --- key performance indicators --- knowledge assets --- knowledge embeddedness --- knowledge specificity --- disruptive innovation --- personalized business mode --- technology acceptance model --- user acceptance --- data analysis --- ontology design --- knowledge management --- heterogeneous architectures --- Big Data --- transformational training programs-TTP --- quality orientation of employees-QOE --- employee loyalty-EL --- universities --- Jordan --- administrative file --- administrative procedure --- sustainability --- open data --- linked data --- provenance --- RDF --- PROV-O --- P-PLAN --- big data --- visualizing --- intellectual structure --- big data environment --- co-citation network --- collaboration network --- sustainability --- bibliometric --- knowledge management --- keywords analysis --- intellectual structure --- emerging trends --- knowledge mapping --- new ventures --- internal social networks --- absorptive capacity --- innovation --- big data --- competitive advantage --- disruptive innovation --- human capital --- innovation --- knowledge management --- sustainability --- smart education --- social networks --- social media --- conceptual maturity model --- technology-enhanced learning process

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