User Intent Classification for Multimedia Information Systems

1. Introduction

1.1. Research questions

1.2. Differentiation (in & out)

1.3. Behavior vs. Intent

1.4. Thesis overview

2. Summary, Conclusion and Future work

3. User Intent Classification

3.1. Methodology

3.1.1. Bayes

3.1.2. Support Vector Machine

3.2. Implementation

3.3. Evalutation

3.4. Example field of application: View Adaptation // ACM MM Paper

4. Related Work

4.1. Search & Retrieval

4.2. Library Science

4.3. Picture Organization

4.4. Annotation (Tags, Keywords)

5. Exploratory Studies for User Intentions // I-KNOW Paper

5.1. Aim

5.2. Approach/Study settings

5.3. Mission/Tasks/ToDo

5.4. Results, Implications & Evaluation

6. Qualitative Taxonomy Analysis

6.1. Aim

6.2. Approach/Settings

6.3. Transcriptions

6.4. Results, Implications & Evaluation

7. A Taxonomy for User Intentions