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Herausgeber: 
  • James Allan
  • Topic Detection and Tracking: Event-based Information Organization 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  November 2012  
    Genre:  EDV / Informatik 
     
    Artificial Intelligence / B / computer science / Data Warehousing / Information Storage and Retrieval / Künstliche Intelligenz / Speech recognition
    ISBN:  9781461353119 
    EAN-Code: 
    9781461353119 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  #12 - The Information Retrieval Series  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  438 gr 
    Seiten:  266 
    Illustration:  XI, 266 p. 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    1 Introduction to Topic Detection and Tracking.- 1 Introduction.- 2 TDT tasks.- 3 History of TDT.- 4 TDT 1999 and TDT.- 5 The Future of TDT.- 2 Topic Detection and Tracking Evaluation Overview.- 1 Introduction.- 2 TDT Definitions: Stories, Events, and Topics.- 3 TDT Corpora.- 4 Evaluation Methodology.- 5 Task Definitions.- 6 Summary.- 3 Corpora for Topic Detection and Tracking.- 1 Introduction.- 2 Overview of TDT Corpus Development.- 3 Collection of Raw Data.- 4 Transcription.- 5 Story Segmentation.- 6 Topic Definition.- 7 Topic Annotation.- 8 Corpus Formats.- 9 Some Properties of the Corpus.- 10 Conclusion.- 4 Probabilistic Approaches to Topic Detection and Tracking.- 1 Introduction.- 2 Core TDT Technologies.- 3 Corpus Processing.- 4 Tracking.- 5 Detection.- 6 Crosslingual TDT.- 7 Conclusions and Future Work.- 8 Acknowledgments.- 5 Multi-strategy Learning for TDT.- 1 Introduction.- 2 Segmentation.- 3 Topic and Event Tracking.- 4 Topic Detection.- 5 First Story Detection.- 6 Story Link Detection.- 7 Multilingual TDT.- 8 Concluding Remarks.- 6 Statistical Models of Topical Content.- 1 Introduction.- 2 Models of Story Generation.- 3 Tracking Systems.- 4 Detection System.- 5 Summary.- 7 Segmentation and Detection at IBM.- 1 Story Segmentation.- 2 Topic Detection.- 3 Acknowledgements.- 8 A Cluster-Based Approach to Broadcast News.- 1 Introduction.- 2 Segmentation.- 3 Detection.- 4 Tracking.- 5 Acknowledgements.- 9 Signal Boosting for Translingual Topic Tracking.- 1 Introduction.- 2 The Signal-to-Noise Perspective.- 3 Topic Tracking System Architecture.- 4 Contrastive Conditions.- 5 Conclusions and Future Work.- 6 Acknowledgments.- 10 Explorations Within Topic Tracking and Detection.- 1 Introduction.- 2 Basic System.- 3 Tracking.- 4 Cluster Detection.- 5 First Story Detection.- 6 Link Detection.- 7 Bounds on Effectiveness.- 8 Automatic Timeline Generation.- 9 Conclusions.- 11 Towards a "Universal Dictionary" for Multi-Language IR Applications.- 1 Introduction.- 2 Our TDT tracking algorithm.- 3 The "Universal Dictionary" experiment.- 4 Conclusions and Directions for Future Work.- 12 An NLP & IR Approach to Topic Detection.- 1 Introduction.- 2 General System Framework.- 3 Representation of News Stories and Topics.- 4 Similarity and Interpretation of a Two-threshold Method.- 5 Multilingual Topic Detection.- 6 Development Experiments.- 7 Evaluation.- 8 Discussion.- 9 Concluding Remarks and Future Works.

      



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