Formulating Complex Queries Using Templates

• Main Author: Zhang, Hao
• Language: en
• Published: 2009
• Subjects: Information Retrieval; User Study; Complex Information needs; Query Templates; Management Sciences
• Online Access: http://hdl.handle.net/10012/4248

While many users have relatively general information needs, users who are familiar with a certain topic may have more specific or complex information needs. Such users already have some knowledge of a subject and its concepts, and they need to find information on a specific aspect of a certain entity, such as its cause, effect, and relationships between entities. To successfully resolve this kind of complex information needs, in our study, we investigated the effectiveness of topic-independent query templates as a tool for assisting users in articulating their information needs. A set of query templates, which were written in the form of fill-in-the-blanks was designed to represent general semantic relationships between concepts, such as cause-effect and problem-solution. To conduct the research, we designed a control interface with a single query textbox and an experimental interface with the query templates. A user study was performed with 30 users. Okapi information retrieval system was used to retrieve documents in response to the users’ queries. The analysis in this paper indicates that while users found the template-based query formulation less easy to use, the queries written using templates performed better than the queries written using the control interface with one query textbox. Our analysis of a group of users and some specific topics demonstrates that the experimental interface tended to help users create more detailed search queries and the users were able to think about different aspects of their complex information needs and fill in many templates. In the future, an interesting research direction would be to tune the templates, adapting them to users’ specific query requests and avoiding showing non-relevant templates to users by automatically selecting related templates from a larger set of templates.