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Geographic Relevance For Travel Search: The 2014-2015 Harvey Mudd College Clinic Project For Expedia, Inc., Hannah Long
Geographic Relevance For Travel Search: The 2014-2015 Harvey Mudd College Clinic Project For Expedia, Inc., Hannah Long
Scripps Senior Theses
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 …
The Future Of Ios Development: Evaluating The Swift Programming Language, Garrett Wells
The Future Of Ios Development: Evaluating The Swift Programming Language, Garrett Wells
CMC Senior Theses
Swift is a new programming language developed by Apple for creating iOS and Mac OS X applications. Intended to eventually replace Objective-C as Apple’s language of choice, Swift needs to convince developers to switch over to the new language. Apple has promised that Swift will be faster than Objective-C, as well as offer more modern language features, be very safe, and be easy to learn and use. In this thesis I test these claims by creating an iOS application entirely in Swift as well as benchmarking two different algorithms. I find that while Swift is faster than Objective-C, it does …
Exploring Algorithmic Musical Key Recognition, Nathan J. Levine
Exploring Algorithmic Musical Key Recognition, Nathan J. Levine
CMC Senior Theses
The following thesis outlines the goal and process of algorithmic musical key detection as well as the underlying music theory. This includes a discussion of signal-processing techniques intended to most accurately detect musical pitch, as well as a detailed description of the Krumhansl-Shmuckler (KS) key-finding algorithm. It also describes the Java based implementation and testing process of a musical key-finding program based on the KS algorithm. This thesis provides an analysis of the results and a comparison with the original algorithm, ending with a discussion of the recommended direction of further development.