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zvelo Introduces Enhanced Content Categorization
  • USA - English


News provided by

zvelo

Jul 29, 2016, 08:30 ET

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Greenwood Village, Colorado (PRWEB) July 29, 2016 -- zvelo, the leading provider of website and device categorization, today announced the delivery of the enhanced Content dataset on the zveloDP. The enhancements of the Content dataset extends zvelo’s market leadership position established over the past decade of the most accurate and broadest coverage content categorization offering available.

zvelo is extending its best-in-class accuracy to the granularity of the web page, blog post, user comment, article and even unstructured content such as Tweets and other social media postings. – Jeff Finn, CEO, zvelo, Inc.

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“The release of the enhanced Content dataset raises the bar even further for the market,” stated Jeff Finn, zvelo’s CEO. “With the newly released Content dataset, zvelo is extending its best-in-class accuracy to the granularity of the web page, blog post, user comment, article and even unstructured content such as Tweets and other social media postings.”

The Content dataset is just one of several a la carte datasets available for subscription from the zveloDP platform and provides the following capabilities:

• Comprehensive Taxonomy – with nearly 500 content categories, the zveloDP Content dataset covers every IAB, MRC, OpenRTB, web filtering and parental controls category set imaginable.
• Extensive language support – the zveloDP Content dataset supports over 200 languages, using a combination of AI-based content categorization, Machine Learning and human-supervised quality assurance and advanced “supervised learning” techniques.
• Page/Post/Article level granularity – the zveloDP Content dataset can provide categorizations at the individual web page, blog post, news article level.
• Unstructured Content and Tweet categorization – the zveloDP Content dataset harnesses the power of the zveloAPI, generating Content categorizations from the submission of unstructured data, such as Tweets and other social media posts.
• Objectionable – exceptionally accurate, high-speed detection of porn, adult, violence, and related objectionable content for use with Brand Safety, Contextual Targeting, Web Filtering and Parental Controls applications.
• Malicious – includes compromised, malware, phishing, fraud, and spyware detections at the page, IP, and host level and includes file-level detections for desktop and mobile web.
zveloDP’s Content dataset is accessible through zveloAPI, which provides simple, scalable and flexible integration and distribution across virtually every deployment environment, from premise-based to small business, enterprise, data centers, and network-level/ISPs. The Content dataset is the foundation for many of the market’s leading web filtering, parental controls, subscriber analytics and brand safety vendors.

To learn more about zveloDP and the available datasets, please visit https://zvelo.com/zvelo-products/zvelos-data-platform-zvelodp/

About zvelo, Inc.
As a proven market leader for content and device categorization, as well as malicious and botnet detection, zvelo is the trusted partner for the market’s preeminent ad tech, network security, and mobile service provider/subscriber analytics vendors. zvelo solves a diverse range of client business needs including providing the foundational datasets for web filtering, parental controls, brand safety, contextual targeting, subscriber analytics and ad fraud prevention.

zvelo, headquartered in Denver, Colorado, is committed to providing the market’s highest quality data products and best responsiveness. The company has additional offices in the Philippines, Spain, and Florida.

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To receive more information about this topic, or schedule an interview, contact James Barker at (720) 897-8113 or email: press(at)zvelo(dot)com.

Corporate Information:
zvelo, Inc.
8350 East Crescent Parkway, Suite 450
Greenwood Village, CO 80111
Phone: (720) 897-8113
zvelo.com or pr(at)zvelo(dot)com

James Barker, zvelo, http://www.zvelo.com, +1 720-259-0255 Ext: 122, [email protected]

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