Semantic vs term-based query modification analysis

Previous research has studied query modifications on a syntactic level by focusing on the addition, elimination and substitution of terms between consecutive queries that have at least one term in common. In this paper, we determine semantic relations between queries by first mapping them onto concepts in linked data sources and then identifying the relations between the concepts. This enables us to find relations between queries that do not share any terms. Moreover, with this approach we can find more detailed and more meaningful query modification patterns than with a term-based analysis. Application of our method to search logs of two search engines shows the importance of studying query modifications on a semantic level. Our results indicate that users often search for entities that are related semantically, but not syntactically. Specifically, users often successively search for two entities sharing a common property, such as two actors starring in the same movie, or two entities with a specific relation, such as spouses. We discuss the implications of these findings for the design of search engines.