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Introduction. The concept of relevance lies at the heart of intellectual access and information retrieval, indeed of reasoning and communication in general; in turn, topical relevance lies at the heart of relevance. The common view of topical relevance is limited to topic matching, resulting in information retrieval systems' failure to detect more complex topical connections which are needed to respond to diversified user situations and tasks.
Method. Based on the role a piece of information plays in the overall structure of an argument, we have identified four topical relevance types: Direct, Indirect (circumstantial), Context, and Comparison. In the process of creating a speech retrieval test collection, graduate history students made 27,000 topical relevance assessments between Holocaust survivor interview segments and real user topics, using the four relevance types, each on a scale of 0 - 4. They recorded justifications for their assessments and kept detailed Topic Notes.
Analysis. We analysed these relevance assessments using a grounded theory approach to arrive at a finer classification of topical relevance types.
Results. For example, indirect relevance(a piece of information is connected to the topic indirectly through inference, circumstantial evidence) was refined to Generic Indirect Relevance, Backward Inference (abduction), Forward Inference (deduction), and Inference from Cases (induction), with each subtype being further illustrated and explicated by examples.
Conclusion. Each of these refined types of topical relevance plays a special role in reasoning, making a conclusive argument, or performing a task. Incorporating them into information retrieval systems allows users more flexibility and a better focus on their tasks. They can also be used in teaching reasoning skills.
