Comprehensibility is an important quality aspect of documents. Incomprehensible documents are of little utility to readers even if they are relevant. However, for many difficult queries such as technical ones, the topically relevant documents tend to be characterized by poor comprehensibility. This makes it difficult for users to satisfy their information needs when searching for documents about difficult topics. In this paper, we propose a novel approach to search for documents that explain query topics and are easy to understand for average users. In particular, we measure the comprehensibility and the relevance of documents based on the concept of Query Domain Graph constructed from Wikipedia articles related to the query. For estimating document comprehensibility we use the frequency and density of difficult terms within documents as well as we utilize graph-based document representation. We then propose retrieval techniques that balance the relevance and comprehensibility based on the concept of difficult word substitution, in which difficult words are replaced by the sets of easy and related words.
['Kouichi Akamatsu', 'Adam Jatowt', 'Katsumi Tanaka']
Towards Solving Comprehensibility-Relevance Trade-off in Information Retrieval