Mood tags and annotation games

Date of Publication

2012

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Computer Science

Subject Categories

Computer Sciences

College

College of Computer Studies

Department/Unit

Computer Science

Thesis Adviser

Nelson Marcos

Defense Panel Member

Arturo Caronongan, III.

Chelsea Celestino

Abstract/Summary

Many people rely on the internet to find the almost everything they need from news article to downloadable contents. Labelling, or tagging, these objects with keywords has enabled users and information retrieval systems in locating these files in the internet. Music is one of the most downloadable content in the internet and relies on subjective human perceptions to be labelled properly. The use of annotation games has helped music information retrieval researchers study user music tags collected from these games by providing a closed/controlled environment for the user to tag presented sound clips. The approach presented here will make use of the concept of an existing annotation game but will be modified to allow users to semantically label their mood to a presented music clip. The game serves more of a prototype to the method that is introduced in this paper. The research aims to associate certain genre used to generally describe a song to a mood tag to describe the songs through the use of data mining techniques to derive certain form of knowledge from the collected tags. The mood tags used in the game are derived from Hevner's adjective cycle.

Abstract Format

html

Language

English

Format

Print

Accession Number

TU18531

Shelf Location

Archives, The Learning Commons, 12F, Henry Sy Sr. Hall

Physical Description

177, 36 leaves: ; illustrations (some colored) ; 28 cm.

Keywords

Data structures (Computer science); Information storage and retrieval systems

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