Text Data Mining
- Indbinding:
- Paperback
- Sideantal:
- 376
- Udgivet:
- 24. maj 2022
- Udgave:
- 22001
- Størrelse:
- 155x20x235 mm.
- Vægt:
- 638 g.
- Ukendt - mangler pt..
Normalpris
Abonnementspris
- Rabat på køb af fysiske bøger
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Text Data Mining
This book discusses various aspects of text data mining. Unlike other books that focus on machine learning or databases, it approaches text data mining from a natural language processing (NLP) perspective.
The book offers a detailed introduction to the fundamental theories and methods of text data mining, ranging from pre-processing (for both Chinese and English texts), text representation and feature selection, to text classification and text clustering. It also presents the predominant applications of text data mining, for example, topic modeling, sentiment analysis and opinion mining, topic detection and tracking, information extraction, and automatic text summarization. Bringing all the related concepts and algorithms together, it offers a comprehensive, authoritative and coherent overview.
Written by three leading experts, it is valuable both as a textbook and as a reference resource for students, researchers and practitioners interested in text data mining. It can also be used for classes on text data mining or NLP.
The book offers a detailed introduction to the fundamental theories and methods of text data mining, ranging from pre-processing (for both Chinese and English texts), text representation and feature selection, to text classification and text clustering. It also presents the predominant applications of text data mining, for example, topic modeling, sentiment analysis and opinion mining, topic detection and tracking, information extraction, and automatic text summarization. Bringing all the related concepts and algorithms together, it offers a comprehensive, authoritative and coherent overview.
Written by three leading experts, it is valuable both as a textbook and as a reference resource for students, researchers and practitioners interested in text data mining. It can also be used for classes on text data mining or NLP.
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Bogen Text Data Mining findes i følgende kategorier:
- Business og læring > Computer og IT
- Databehandling og informationsteknologi > Databaser > Data mining
- Databehandling og informationsteknologi > Informatik > Kunstig intelligens > Ekspertsystemer og vidensbaserede systemer
- Databehandling og informationsteknologi > Informatik > Kunstig intelligens > Naturligt sprog og maskinoversættelse
- Databehandling og informationsteknologi > Informatik > Kunstig intelligens > Machine learning
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