Related APIs in Category: Mapping
What is Widevine DRM? Widevine's DRM solution combines the following industry adopted standards to provide robust multiplatform content protection: Dynamic Adaptive Streaming over HTTP (DASH) DASH enables streaming of high quality media content over the Internet. DASH leverages standard HTTP protocol and can be easily deployed on existing Internet infrastructure (web servers, CDNs, firewalls, etc). Common Encryption (CENC) CENC is an industry standards based approach to content encryption. CENC identifies standard encryption and key mapping mechanisms that may be utilized by one or more DRM systems to allow the decryption of the same file using different DRM systems. CENC enables content providers to encrypt their content once and deliver it to numerous client devices and their assorted DRM schemes. Encrypted Media Extensions (EME) EME is a proposed W3C standard that provides a set of common APIs that can be used to interact with DRM systems and manage license key exchange. EME allows content providers to design a single application solution for all devices. Key benefits of Widevine's DRM solution: Support for reliable content protection across multiple systems:. Provides ubiquitous device coverage and extends synergy across multiple content protection systems. See a list of currently supported platforms. Complete control and flexibility during video playback: Fully featured HTML5 video player with adaptive streaming, QoS, and accessibility support across devices.
Chicmi are mapping out the fashion scene in the world's fashion cities, starting with London, Glasgow, Edinburgh and Manchester. Use the Chicmi API to access our unique set of fashion data, including every fashion sale, sample sale, fashion exhibition and fashion event in each city.
JSONpedia API is designed to simplify access at MediaWiki contents transforming everything into JSON. Such API provides a REST service to parse, convert, and enrich WikiText documents. JSONpedia supplies capabilities for recursive template expansion and mapping to DBpedia. This framework has been designed to extract linguistic resources from the Wikipedia and to enable massive data scraping. Our mission is to deliver a general purpose infrastructure for Wikipedia multi language data consumption both for researchers and industry.
API AI provides a way to create mapping between language structures that are common in natural languesgea and data structures that are easy for software to parse and take action. Once these mappings have been created, you can make a query with either natural languages text or a voice sound file, and API.AI will return structured data with an action to take the parameters to act upon.