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Bücher Englische Bücher Wissen & Bildung Naturwissenschaft, Medizin, Informatik, Technik Informatik & EDV Informatik Knowledge Discovery from Multi-Sourced Data
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Knowledge Discovery from Multi-Sourced Data
Chen Ye, Hongzhi Wang, Guojun Dai (Broschiert, Englisch)
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Beschreibung
This book addresses several knowledge discovery problems on multi-sourced data where the theories, techniques, and methods in data cleaning, data mining, and natural language processing are synthetically used. This book mainly focuses on three data models: the multi-sourced isomorphic data, the multi-sourced heterogeneous data, and the text data. On the basis of three data models, this book… studies the knowledge discovery problems including truth discovery and fact discovery on multi-sourced data from four important properties: relevance, inconsistency, sparseness, and heterogeneity, which is useful for specialists as well as graduate students. Data, even describing the same object or event, can come from a variety of sources such as crowd workers and social media users. However, noisy pieces of data or information are unavoidable. Facing the daunting scale of data, it is unrealistic to expect humans to “label” or tell which data source is more reliable.Hence, it is crucial to identify trustworthy information from multiple noisy information sources, referring to the task of knowledge discovery. At present, the knowledge discovery research for multi-sourced data mainly faces two challenges. On the structural level, it is essential to consider the different characteristics of data composition and application scenarios and define the knowledge discovery problem on different occasions. On the algorithm level, the knowledge discovery task needs to consider different levels of information conflicts and design efficient algorithms to mine more valuable information using multiple clues. Existing knowledge discovery methods have defects on both the structural level and the algorithm level, making the knowledge discovery problem far from totally solved. 53,49 €
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Technische Daten
Erscheinungsdatum
15.06.2022
Sprache
Englisch
EAN
9789811918780
Herausgeber
Springer Singapore
Serien- oder Bandtitel
SpringerBriefs in Computer Science
Sonderedition
Nein
Autor
Chen Ye, Hongzhi Wang, Guojun Dai
Seitenanzahl
83
Auflage
1
Einbandart
Broschiert
Schlagwörter
Truth Discovery, Source Reliability, Integrity Constraints, Optimization Framework, Fact Extraction, Data Fusion, Data Integration, Deep Learning
Thema-Inhalt
UNF - Data Mining
UYQE - Wissensbasierte Systeme, Expertensysteme
UN - Datenbanken
Höhe
235 mm
Breite
15.5 cm
Hersteller: Springer Nature Customer Service Center GmbH, ProductSafety@springernature.com
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