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

TL;DR

This paper presents a Bayesian method to infer users' informational goals from free-text queries in consumer software, improving understanding of user intent by modeling language and goal relationships.

Contribution

It introduces a Bayesian framework for mapping natural language queries to user goals, with extensions incorporating language structure and distinctions.

Findings

Effective modeling of user queries and goals

Enhanced accuracy with language structure integration

Flexible Bayesian approach adaptable to various user intents

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.