Of the Dissertation Automatic Assessment of Non - Topical Properties of Text by Machine Learning Methods

..............................................................................................ii Acknowledgements .................................................................................iv List of Tables ......................................................................................viii List of Figures ........................................................................................x Chapter 1: Introduction...................................................................................................1 Chapter 2: Non-Topical Qualitative Properties of Documents....................................7 2.1 User – Centered Studies....................................................................................... 8 2.2 Information – Centered Studies ......................................................................... 10 2.3 Summary of Properties ...................................................................................... 11 2.4 Assessment of Qualitative Properties ................................................................ 14 Chapter 3: Linguistic Features......................................................................................17 3.1 Stylistic Studies.................................................................................................. 17 3.1.1 Authorship Attribution Research ................................................................. 18 3.1.2 Genre Classification..................................................................................... 19 3.1.3 “Style” and Non-topical Qualitative Properties........................................... 20 3.2 Linguistic Features as Indicators ....................................................................... 21 Chapter 4: Automatic Classification Techniques........................................................24 4.1 Classification through Learning......................................................................... 25 4.2 Linear Regression .............................................................................................. 27 4.3 Logistic Regression............................................................................................ 28 4.4 Decision Tree Learning...................................................................................... 30 4.5 Support Vector Machines (SVMs)..................................................................... 34 4.6 Applications ....................................................................................................... 35 Chapter 5: Research Problems......................................................................................38 Chapter 6: Methodology, Experimental Design and Evaluation Measures..............41 6.1 Document Corpora............................................................................................. 41 6.2 Non-Topical Qualitative Property Judgments ................................................... 43