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Full-Text Articles in Databases and Information Systems
Music Genre Classification Capabilities Of Enhanced Neural Network Architectures, Joshua Engelkes
Music Genre Classification Capabilities Of Enhanced Neural Network Architectures, Joshua Engelkes
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
With the increase of digital music audio uploads, applications that deal with music information have been widely requested by streaming platforms. Automatic music genre classification is an important function of music recommendation and music search applications. Since the music genre categorization criteria continually shift, data-driven methods such as neural networks have been proven especially useful to music information retrieval. An enhanced CNN architecture, the Bottom-up Broadcast Neural Network, uses mel-spectrograms to push music data through a network where important low-level information is preserved. An enhanced RNN architecture, the Independent Recurrent Neural Network for Music Genre Classification, takes advantage of the …
Querying Large Databases, Nathan Beneke
Querying Large Databases, Nathan Beneke
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
This paper investigates two approaches to improving query times on large relational databases. The first technique capitalizes on the knowledge of a database's structures and properties one typically has. This technique can execute some queries exactly in a constant, bounded amount of time. When this technique cannot be used to exactly execute a query we show how it can still be used to drastically lower the run-time on the query while getting a good approximation of the exact result. We also discuss the complexity of deciding whether a query is evaluable in this way, both theoretically and practically. The second …