The QueRIE system for Personalized Query Recommendations Gloria Chatzopoulou 1 Magdalini Eirinaki 2 Suju Koshy 2 Sarika Mittal 2 Neoklis Polyzotis 3 Jothi Swarubini Vindhiya Varman 2 1 Vanderbilt University 2 San Jose State University 3 UC Santa Cruz Abstract Interactive database exploration is a key task in information mining. However, users who lack SQL expertise or familiarity with the database schema face great difficulties in performing this task. To aid these users, we developed the QueRIE system for personalized query recommendations. QueRIE continuously monitors the user’s querying behavior and finds matching patterns in the system’s query log, in an attempt to identify previous users with similar information needs. Subsequently, QueRIE uses these “similar” users and their queries to recommend queries that the current user may find interesting. We discuss the key components of QueRIE and describe empirical results based on actual user traces with the Sky Server database. 1 Introduction Database systems are becoming increasingly popular in the scientific community, as tools to access and ana- lyze large volumes of scientific data. Prominent examples include the Genome browser 1 that hosts a genomic database, and SkyServer 2 that stores large volumes of astronomical measurements. Such databases are typically accessed through a web interface that allows users to pose queries through forms or in some declarative query language (e.g., SkyServer users can submit SQL queries directly). Despite the availability of querying tools, users of these systems may still find it challenging to discover in- teresting information. Specifically, users may not know which parts of the database hold useful information, may overlook queries that retrieve relevant data or might not have the required expertise to formulate such queries. An exhaustive exploration of the database is also practically impossible, due to the continuously growing size of the data. To address this issue, we designed the QueRIE 3 system that assists users in the interactive exploration of a large database. The core idea is to present a user with personalized query recommendations, which are relevant to the user’s information needs and can serve as “templates” for query formulation. The user is able to directly submit or further refine these queries, instead of having to compose new ones. QueRIE is built on a simple premise that is inspired by Web recommender systems: If a user A has similar querying behavior to user B, then they are likely interested in retrieving the same data. Hence, the queries of Copyright 2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering 1 http://genome.ucsc.edu/ 2 http://cas.sdss.org/ 3 Query Recommendations for Interactive data Exploration 1