Identifying Queries in Instant Search Logs

Query logs of search engines with instant search functionality are challenging for log analysis, since the log entries represent interactions at the keystroke level, rather than at the query level. To enable log analyses at the query level, a user's logged sequence of keystroke-level interactions needs to be mapped to distinct queries. This problem bears strong parallels to session detection in "standard" query logs (i.e., forming groups of subsequent queries on the same topic), but there are salient differences. In this paper, we present a new approach to identifying interactions belonging to the same query in instant query logs. In an experimental comparison, our new approach achieves an F-2 score of 0.93 compared to only 0.83 of a state-of-the-art cascading method for query log session detection.