19 citations · 20 across the 3 of their papers we have counts for
6 papers · 1 filter
Using Large Language Models to Generate, Validate, and Apply User Intent Taxonomies
Chirag Shah, Ryen W. White, Reid Andersen +13
Log data can reveal valuable information about how users interact with Web search services, what they want, and how satisfied they are. However, analyzing user intents in log data…
Users' Perception of Search Engine Biases and Satisfaction
Bin Han, Chirag Shah, Daniel Saelid
Search engines could consistently favor certain values over the others, which is considered as biased due to the built-in infrastructures. Many studies have been dedicated to detec…
Reading Protocol: Understanding what has been Read in Interactive Information Retrieval Tasks
Daniel Hienert, Dagmar Kern, Matthew Mitsui +2
In Interactive Information Retrieval (IIR) experiments the user's gaze motion on web pages is often recorded with eye tracking. The data is used to analyze gaze behavior or to iden…
Data Requirements for Evaluation of Personalization of Information Retrieval - A Position Paper
Nicholas J. Belkin, Daniel Hienert, Philipp Mayr +1
Two key, but usually ignored, issues for the evaluation of methods of personalization for information retrieval are: that such evaluation must be of a search session as a whole; an…
The Role of the Task Topic in Web Search of Different Task Types
Daniel Hienert, Matthew Mitsui, Philipp Mayr +2
When users are looking for information on the Web, they show different behavior for different task types, e.g., for fact finding vs. information gathering tasks. For example, relat…
Toward Collaborative Information Seeking (CIS)
Chirag Shah
It is natural for humans to collaborate while dealing with complex problems. In this article I consider this process of collaboration in the context of information seeking. The stu…