1.6 Overview of the Thesis

• Chapter 2 - Related Work — We survey, identify, and describe related work for leveraging concept languages for information access.
• Chapter 3 - Experimental Methodology — The basic building blocks pertaining to the evaluation of information retrieval experiments, the test collections we use in the thesis, and the setting of various parameters are presented.
• Chapter 4 - Query Modeling Using Feedback Information — We look at and evaluate various query modeling methods for relevance feedback in the context of generative language models. We explicate the relation between two popular models and introduce two novel methods that estimate a query model using information from each feedback document individually and combined. While most previous approaches focus either on features of the entire set or of the individual relevant documents, our models exploit features of both.
• Chapter 5 - Query Modeling Using Concepts — We then turn to using concept languages to estimate a query model. In this chapter we propose generative concept models as an extension to query modeling within the language modeling framework, which leverages manual document annotations using controlled vocabularies to improve retrieval. By means of relevance feedback the original query is translated into a conceptual representation, which is subsequently used to update the query model.
• Chapter 6 - Linking Queries to Concepts — Next, we take a closer look at identifying relevant concepts with respect to a user’s query. In the previous chapter we used existing document annotations and relevance feedback to obtain concepts for queries. In this chapter we look at how we can apply supervised machine learning models to this task and compare it to several baseline methods including a straightforward lexical match and a purely retrieval based approach.
• Chapter 7 - Query Modeling Using Linked Concepts — In this chapter we bring techniques from the previous chapters together. We apply the supervised machine learning method presented in Chapter 6 to queries associated with two web-scale test collections. We link each query to Wikipedia articles and apply the ideas presented in Chapters 4 and 5 to estimate a query model.
• Chapter 8 - Conclusions and Future Work — Here we summarize our contributions and describe potential areas for future work.

Chapter 2 and Chapter 3 serve as introductory chapters to the field of information retrieval, language modeling for information retrieval, mapping free text to structured knowledge sources, and experimental evaluation in the context of information retrieval. We recommend that the reader first get familiarized with the material presented there before reading other chapters. Many of the contributions made in the thesis converge in Chapter 7 and to be able to appreciate the results presented there, we encourage the reader to start with earlier material, in particular with Chapter 4 and Chapter 6. In appendix A (See page 477), we include a nomenclature and list of abbreviations.