Active Faceted Search

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Title: Active Faceted Search
Author: Weber, Sean
Contributor: University of Helsinki, Faculty of Science
Publisher: Helsingin yliopisto
Date: 2020
Language: eng
Thesis level: master's thesis
Discipline: Algorithms and Machine Learning
Abstract: We present Active Faceted Search, a technique which allows a user to iteratively refine search results by selecting from a set of facets that is dynamically refined with each iteration. The facets presented are selected using a contextual multi armed bandit model. We first describe the computational model of a system which implements Active Faceted Search. We also create a web application to demonstrate an example of a system that can use an active faceted search component along with more traditional search elements such as a typed query and sidebar component. We perform simulations to compare the performance of the system under different parameters. Finally, we present a user experiment in which users are instructed to perform tasks in order to compare Active Faceted Search to traditional search techniques.
Subject: faceted search
exploratory search

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