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Event Mining for Explanatory Modeling

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Title: Event Mining for Explanatory Modeling
Description: This book introduces the concept of Event Mining for building explanatory models from analyses of correlated data. Such a model may be used as the basis for predictions and corrective actions. The idea is to create, via an iterative process, a model that explains causal relationships in the form of structural and temporal patterns in the data. The first phase is the data-driven process of hypothesis formation, requiring the analysis of large amounts of data to find strong candidate hypotheses. The second phase is hypothesis testing, wherein a domain expert's knowledge and judgment is used to test and modify the candidate hypotheses. The book is intended as a primer on Event Mining for data-enthusiasts and information professionals interested in employing these event-based data analysis techniques in diverse applications. The reader is introduced to frameworks for temporal knowledge representation and reasoning, as well as temporal data mining and pattern discovery. Also discussed are the design principles of event mining systems. The approach is reified by the presentation of an event mining system called EventMiner, a computational framework for building explanatory models. The book contains case studies of using EventMiner in asthma risk management and an architecture for the objective self. The text can be used by researchers interested in harnessing the value of heterogeneous big data for designing explanatory event-based models in diverse application areas such as healthcare, biological data analytics, predictive maintenance of systems, computer networks, and business intelligence.
Authors: Laleh Jalali, Ramesh Jain
Resource Type: eBook.
Subjects: Computer simulation, Data logging, Data mining
Categories: COMPUTERS / System Administration / Storage & Retrieval, COMPUTERS / Data Science / General, COMPUTERS / Data Science / Machine Learning
Database: eBook Collection (EBSCOhost)
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  – Type: ebook-epub
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Header DbId: nlebk
DbLabel: eBook Collection (EBSCOhost)
An: 3319091
RelevancyScore: 1103
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 1103.19409179688
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  Data: Event Mining for Explanatory Modeling
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  Data: This book introduces the concept of Event Mining for building explanatory models from analyses of correlated data. Such a model may be used as the basis for predictions and corrective actions. The idea is to create, via an iterative process, a model that explains causal relationships in the form of structural and temporal patterns in the data. The first phase is the data-driven process of hypothesis formation, requiring the analysis of large amounts of data to find strong candidate hypotheses. The second phase is hypothesis testing, wherein a domain expert's knowledge and judgment is used to test and modify the candidate hypotheses. The book is intended as a primer on Event Mining for data-enthusiasts and information professionals interested in employing these event-based data analysis techniques in diverse applications. The reader is introduced to frameworks for temporal knowledge representation and reasoning, as well as temporal data mining and pattern discovery. Also discussed are the design principles of event mining systems. The approach is reified by the presentation of an event mining system called EventMiner, a computational framework for building explanatory models. The book contains case studies of using EventMiner in asthma risk management and an architecture for the objective self. The text can be used by researchers interested in harnessing the value of heterogeneous big data for designing explanatory event-based models in diverse application areas such as healthcare, biological data analytics, predictive maintenance of systems, computer networks, and business intelligence.
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RecordInfo BibRecord:
  BibEntity:
    Classifications:
      – Code: 006.312
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Computer simulation
        Type: general
      – SubjectFull: Data logging
        Type: general
      – SubjectFull: Data mining
        Type: general
    Titles:
      – TitleFull: Event Mining for Explanatory Modeling
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Laleh Jalali
      – PersonEntity:
          Name:
            NameFull: Ramesh Jain
      – PersonEntity:
          Name:
            NameFull: Laleh Jalali
      – PersonEntity:
          Name:
            NameFull: Ramesh Jain
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2021
            – D: 17
              M: 03
              Type: profile
              Y: 2023
          Identifiers:
            – Type: isbn-print
              Value: 9781450384834
            – Type: isbn-electronic
              Value: 9781450384858
            – Type: isbn-electronic
              Value: 9781450384841
          Titles:
            – TitleFull: Event Mining for Explanatory Modeling
              Type: main
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