Please use this identifier to cite or link to this item:
Title: Large scale music information retrieval by semantic tags
Keywords: Music, tag recommendation, explicit multiple attributes, search
Issue Date: 12-Jul-2010
Citation: ZHAO ZHEN DONG (2010-07-12). Large scale music information retrieval by semantic tags. ScholarBank@NUS Repository.
Abstract: Model-driven and Data-driven methods are two widely adopted paradigms in Query by Description (QBD) music search engines. Model-driven methods attempt to learn the mapping between low-level features and high-level music semantic meaningful tags, the performance of which are generally affected by the well-known semantic gap. On the other hand, Data-driven approaches rely on the large amount of noisy social tags annotated by users. In this thesis, we focus on how to design a novel Model-driven method and combine two approaches to improve the performance of music search engines. With the increasing number of digital tracks appear on the Internet, our system is also designed for large-scale deployment, on the order of millions of objects. For processing large-scale music data sets, we design parallel algorithms based on the MapReduce framework to perform large-scale music content and social tag analysis, train a model, and compute tag similarity. We evaluate our methods on CAL-500 and a large-scale data set (N = 77, 448 songs) generated by crawling Youtube and Our results indicate that our proposed method is both effective for generating relevant tags and efficient at scalable processing. Besides, we also have implemented a web-based prototype music retrieval system as a demonstration.
Appears in Collections:Master's Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
Zhao_Zhendong_Master_SoC_LargeScaleMusicRetrievalbySemanticTags_2010.pdf1.28 MBAdobe PDF



Page view(s)

checked on Apr 18, 2019


checked on Apr 18, 2019

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.