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Tech News (more headlines) 07-26-2014

Senzari Unveils MusicGraph.ai At The GraphLab Conference 2014

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Website: http://developer.musicgraph.com

Senzari introduced MusicGraph.ai, the first web-based graph analytics and intelligence engine for the music industry at the GraphLab Conference 2014, the annual gathering of leading data scientists and machine learning experts. MusicGraph.ai will serve as the primary dashboard for MusicGraph, where API clients will be able to view detailed reports on their API usage and manage their account. More importantly, through this dashboard, they will also be able to access a comprehensive library of algorithms to extract even more value from the world's most extensive repository of music data.

"We believe MusicGraph.ai will forever change the music intelligence industry, as it allows scientists to execute powerful analytics and machine learning algorithms at scale on a huge data-set without the need to write a single-line of code"

"We believe MusicGraph.ai will forever change the music intelligence industry, as it allows scientists to execute powerful analytics and machine learning algorithms at scale on a huge data-set without the need to write a single-line of code," explained Demian Bellumio, COO of Senzari. In the coming weeks, Senzari's MusicGraph API clients - which includes hundreds of companies, including streaming service providers, record labels, and music researchers - will be able to login, select the data they want, choose from dozens of proven algorithms, and run them on an elastic computing environment with as many machines as they wish - all within just a few minutes. "No more time and money wasted on finding, cleansing, and storing this hard-to-find music data, and especially, on the engineering effort needed to operate these complex graph computing infrastructure - which require deep domain expertise and PhD-level talent," Bellumio said.

MusicGraph.ai seamlessly integrates leading Big Data technologies, including Titan with Cassandra and Elasticsearh for the distributed graph database system, Hadoop and Spark for parallel processing, and GraphLab and GraphX as algorithmic engines. The algorithms will be divided in two distinct sets, Analytics and Intelligence. Analytics will initially include a set of popular "graph analytics" algorithms such as PageRank, connected components, and triangle counting. Intelligence will incorporate powerful "machine learning" algorithms, such as collaborative filtering, k-means, logistic regression, and support vector machines (SVMs). In some instances, the user will be able to run the same algorithm from multiple engines, like GraphLab and GraphX, to compare the results and performance across them. In terms of real-world use cases for MusicGraph.ai, data scientists can leverage it to enhance or develop music recommendation services, identify data anomalies, and perform community detection within their networks, among other applications, all in an automated and highly scalable way.

"MusicGraph.ai dramatically opens up the market potential of Senzari's MusicGraph, as we are now not only providing industry leading data and music recommendations services to our partners, but we'll now offer unparalleled access to Big Data infrastructure and tools that they can use to derive actionable data from billions of data points that connect the content and users," commented Bill Hajjar, CEO of Senzari. "We believe that in MusicGraph's first iteration we democratized music data access, and now, with MusicGraph.ai, we are democratizing music knowledge. Most impressively, our team was able to make this leap possible in just months, not years."

All developers and data scientists interested in learning more, can sign up for free access to MusicGraph by visiting http://developer.musicgraph.com.

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