Inferring Informational Goals from Free-Text Queries: A Bayesian Approach

2013/01/30 by David Heckerman, Eric Horvitz, Heckerman, David +2
Computer Science · #Open Source Software Innovations #Software Engineering Research #Software Engineering Techniques and Practices #cs.AI #cs.CL #cs.IR

paper · pdf · doi:10.48550/arxiv.1301.7382

Appears in Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI1998)

arxiv created 2015/05/16 · arxiv updated 2015/05/19

Abstract

People using consumer software applications typically do not use technical jargon when querying an online database of help topics. Rather, they attempt to communicate their goals with common words and phrases that describe software functionality in terms of structure and objects they understand. We describe a Bayesian approach to modeling the relationship between words in a user's query for assistance and the informational goals of the user. After reviewing the general method, we describe several extensions that center on integrating additional distinctions and structure about language usage and user goals into the Bayesian models.

Citations

• The Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users

Cited by

• Bayesian networks and information retrieval: an introduction to the special issue
• SUITOR
• Continual computation policies for utility-directed prefetching

Related

• The Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users
• Interactive Information Need Prediction with Intent and Context
• Large Language Models, Knowledge Graphs and Search Engines: A Crossroads for Answering Users' Questions
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