Improving query suggestion by utilizing user intent

In this paper, we introduce a query suggestion approach to reuse users´ search context and search logs. For a given search log, we integrate two pieces of wisdom embedded in the search context: consecutive queries and reformulation patterns between consecutive queries. When providing suggestions online, we extract concepts that represent the user´s intent and associate these concepts with wisdom attained from past users who had similar search intents. Finally, customized suggestions are provided according to the current user´s search pattern. The experimental results demonstrate that the proposed approach outperforms existing query suggestion methods and effectively provides users with more accurate suggestions to help them get required information faster.