In this article, you will learn more about Exorde and its key features that set it apart from many other similar projects.

The project team offers an ecosystem called Exorde, built around a core platform that provides objective assessments of information trust (and virality-related analytics), which is based on community, artificial intelligence modules, and a token-based economy.

Exorde Platform.

Exorde's working systems are a core component and will serve as the base layer for the entire ecosystem. This platform is decentralized, open and transparent.

Participants here will work together to index the entire network, extracting its unstructured information, relationships, similarities, trends and any type of pattern in the information circulating everywhere on the Internet, regardless of platform or media.

The Exorde platform performs continuous knowledge extraction from the content indexed by its members through continuous and decentralized data analytics.

It is managed through its own DAO (decentralized autonomous organization), which uses community votes and surveys. Management is completely decentralized among all members of the community, be they investors, participants, employees. Collectively, they change internal rules and systems parameters (rewards, limits, delays, scheduling, etc.) AND will have a built-in reputation system. These mechanisms are designed to continuously align community interests and governance for the benefit of the Exorde ecosystem and services.

Functionally, the platform is based on Working Systems, designed by tiers. They act as the digital data factory that powers the Exorde Knowledge Graph, or Exorde Graph:

1) Working Systems: the first level of the system, where participants index various URLs taken from the Internet and their relationships to the data (similarities, correlations) according to predefined rules and guidelines.

This set of rules is established and approved by the Exorde community and can evolve to increase relevance and maximize the value of the data.

2) Data Analysis System: the second level of the system, where participants perform continuous analysis of data of different types on linked and indexed data that constitute the main Exorde database (knowledge graph). It includes data clustering, trend analysis, labeling, tracing, and partitioning, and is performed using sentence-encoding (or document-encoding) NLP models such as BERT (or other transformer-based deep learning models). Text objects (sentences, paragraphs, headings, etc.) are converted into numeric vectors and then added to the underlying neural database, allowing scaling of indexing and queries using Exorde Contributors. These data operations will increase in number and variety over time to match demand and maximize the relevance of Exorde services and products.

Links:
Website: https://exorde.network/
Twitter: https://twitter.com/ExordeLabs
Discord: https://discord.gg/ExordeLabs