9789811918780 - knowledge discovery from multi-sourced data di ye, chen; wang, hongzhi; dai, guojun (20 risultati)
Lingua: Inglese
Editore: Springer, 2022
- Brossura
Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 46,22
EUR 4,00 spedizioneSpedito da Italia a U.S.A.Quantità: 5 disponibili
Condizione: new.
Lingua: Inglese
Editore: Springer Verlag, Singapore, Singapore, 2022
- Brossura
- Prima edizione
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 53,15
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Springer, 2022
- Brossura
Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 60,73
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
Lingua: Inglese
Editore: Springer, 2022
- Brossura
Da: Brook Bookstore, Milano, MI, ItaliaBrook Bookstore
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 41,49
EUR 27,99 spedizioneSpedito da Italia a U.S.A.Quantità: 5 disponibili
Condizione: new.
Lingua: Inglese
Editore: Springer, 2022
- Brossura
Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 61,02
EUR 13,97 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. In.
Lingua: Inglese
Editore: Springer, 2022
- Brossura
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 66,89
EUR 9,50 spedizioneSpedito da Irlanda a U.S.A.Quantità: 15 disponibili
Condizione: New.
Lingua: Inglese
Editore: Springer, 2022
- Brossura
Da: Books Puddle, New York, NY, U.S.A.Books Puddle
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 76,00
EUR 3,46 spedizioneSpedito in U.S.A.Quantità: 4 disponibili
Condizione: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.
Lingua: Inglese
Editore: Springer, 2022
- Brossura
Da: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 83,11
EUR 9,10 spedizioneSpedito in U.S.A.Quantità: 15 disponibili
Condizione: New.
Lingua: Inglese
Editore: Springer Verlag, Singapore, Singapore, 2022
- Brossura
- Prima edizione
Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 83,83
EUR 32,08 spedizioneSpedito da Australia a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Lingua: Inglese
Editore: Springer, Springer, 2022
- Brossura
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 58,39
EUR 60,80 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 dat…a 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.
Altre immaginiLingua: Inglese
Editore: Springer, 2022
- Brossura
Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 50,40
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. Knowledge Discovery from Multi-Sourced Data | Chen Ye (u. a.) | Taschenbuch | xii | Englisch | 2022 | Springer | EAN 9789811918780 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Lingua: Inglese
Editore: Springer Nature Singapore, 2022
- Brossura
Da: Buchpark, Trebbin, GermaniaBuchpark
Contatta il venditoreVenditore con 5 stelleCondizione: Usato
EUR 35,90
EUR 105,00 spedizioneSpedito da Germania a U.S.A.Quantità: 3 disponibili
Condizione: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | 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 t…hree 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.
Lingua: Inglese
Editore: Springer Nature Singapore, 2022
- Brossura
Da: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, GermaniaBUCHSERVICE / ANTIQUARIAT Lars Lutzer
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Molto buono
EUR 179,95
EUR 39,95 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Softcover. Condizione: gut. 2022. Knowledge Discovery from Multi-Sourced Data In deutscher Sprache. pages.
Lingua: Inglese
Editore: Springer, 2022
- Brossura
- Print on Demand
Da: Basi6 International, Irving, TX, U.S.A.Basi6 International
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 61,05
Spedizione gratuitaSpedito in U.S.A.Quantità: 10 disponibili
Condizione: Brand New. New. Delivery takes 20-25 days. Print on Demand.
Knowledge Discovery from Multi-Sourced Data
Ye, Chen (Author)/ Wang, Hongzhi (Author)/ Dai, Guojun (Author)
Lingua: Inglese
Editore: Springer, 2022
- Brossura
- Print on Demand
Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 54,05
EUR 11,66 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: Brand New. 95 pages. 9.25x6.10x0.28 inches. In Stock. This item is printed on demand.
Lingua: Inglese
Editore: Springer Nature Singapore Jun 2022, 2022
- Brossura
- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 53,49
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 focu…ses 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. 96 pp. Englisch.
Lingua: Inglese
Editore: Springer, 2022
- Brossura
- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 75,92
EUR 7,58 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Condizione: New. Print on Demand.
Lingua: Inglese
Editore: Springer, 2022
- Brossura
- Print on Demand
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 77,91
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND.
Lingua: Inglese
Editore: Springer, Berlin|Springer Nature Singapore|Springer, 2022
- Brossura
- Print on Demand
Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 48,37
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 b…ook mainly focuses on three data models: .
Lingua: Inglese
Editore: Springer, Springer Jun 2022, 2022
- Brossura
- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 53,49
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 96 pp. Englisch.
