Most of the latest Web trends (such as Real-time Web, Geo-social Web, etc.) revolve around “things” or “entities” (such as media entities (videos, songs, images, etc.), Points of Interests (POIs), products, updates, etc.). Entities, therefore, are building blocks for a lot of cutting-edge and fast-evolving technologies.
Ziva has developed specialized, patent-pending techniques that help extract “entities” from the Web. Based on these techniques, Ziva has built an index of more than 20 million entities. More and more entities are regularly being added to the repository via a self-learning engine.
Ziva Software combines specialized web-based entity extraction techniques with a flexible data quality pipeline to generate complete and accurate POIs (places-of-interests) and other location-based structured data (such as classifieds, etc.).
Ziva processes and refines Web-scale data by analyzing and mining web fragments with overlapping and/or contradicting information. Ziva identifies and extracts structured information using innovative machine learning techniques.
Ziva has developed specialized, patent-pending techniques that help extract “entities” from the Web. Based on these techniques, Ziva has built an index of more than 20 million entities. More and more entities are regularly being added to the repository via a self-learning engine.
Ziva Software combines specialized web-based entity extraction techniques with a flexible data quality pipeline to generate complete and accurate POIs (places-of-interests) and other location-based structured data (such as classifieds, etc.).
Ziva processes and refines Web-scale data by analyzing and mining web fragments with overlapping and/or contradicting information. Ziva identifies and extracts structured information using innovative machine learning techniques.
