Inferring Informational Goals from Free-Text Queries: A Bayesian Approach
Information Retrieval
2015-05-19 v2 Artificial Intelligence
Computation and Language
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.
Cite
@article{arxiv.1301.7382,
title = {Inferring Informational Goals from Free-Text Queries: A Bayesian Approach},
author = {David Heckerman and Eric J. Horvitz},
journal= {arXiv preprint arXiv:1301.7382},
year = {2015}
}
Comments
Appears in Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI1998)