Graduation Year
2015
Document Type
Open Access Senior Thesis
Degree Name
Bachelor of Arts
Department
Computer Science
Reader 1
Robert Keller
Reader 2
Winston Ou
Terms of Use & License Information
Rights Information
© 2015 Hannah A. Long
Abstract
The purpose of this Clinic project is to help Expedia, Inc. expand the search capabilities it offers to its users. In particular, the goal is to help the company respond to unconstrained search queries by generating a method to associate hotels and regions around the world with the higher-level attributes that describe them, such as “family- friendly” or “culturally-rich.” Our team utilized machine-learning algorithms to extract metadata from textual data about hotels and cities. We focused on two machine-learning models: decision trees and Latent Dirichlet Allocation (LDA). The first appeared to be a promising approach, but would require more resources to replicate on the scale Expedia needs. On the other hand, we were able to generate useful results using LDA. We created a website to visualize these results.
Recommended Citation
Long, Hannah, "Geographic Relevance for Travel Search: The 2014-2015 Harvey Mudd College Clinic Project for Expedia, Inc." (2015). Scripps Senior Theses. 670.
https://scholarship.claremont.edu/scripps_theses/670
