Using Structured Queries for Keyword Information Retrieval

An increasingly important class of keyword search tasks are those where users are looking for a specific piece of information buried within a few documents in a large collection. Examples include searching for someone’s phone number, the schedule for a meet-ing, or a package tracking URL, within a personal email collection. We refer to such tasks as “precision-oriented search tasks”. While modern information extraction techniques can be used to extract the concepts involved in these tasks (persons, phone numbers, sched-ules, etc.), since users only provide keywords as input, the problem of identifying the documents that contain the information of inter-est remains a challenge. In this paper, we propose a solution to this problem based on the concept of automatically generating “interpretations ” of key-word queries. Interpretations are precise structured queries, over the extracted concepts, that model the real intent behind a keyword query. We formalize the notion of interpretations and address the challenges in identifying the most likely interpretations for a given keyword query. We validate the benefits of our approach by pre-senting results both from a user study and experimental compar-isons against an alternative approach. 1