Search Results for "knowledge management"

A cyber-physical systems is a system that collects a variety of data in physical space (the real world), analyzes and converts it into knowledge in cyberspace, and feeds the knowledge back to the real world to revitalize industry and solve social problems. GridDB is an open database that enables real-time processing of vast amounts of time-series data in physical space, which is necessary to realize a cyber-physical system. Multi-model architecture capable of supporting various data stores with time-series data-oriented and pluggable data stores for efficient real-time processing and management of huge amounts of time-series data at high frequency. ...

Unlock the power of big data with OpenDataDiscovery Platform. Experience seamless end-to-end insights, powered by unprecedented observability and trust - from ingestion to production - while building your ideal tech stack! Democratize data and accelerate insights. Find data that fits your use case and discover hints left by your peers to leverage existing knowledge. Explore tags, ownership details, links to other sources and other information to shorten and simplify data discovery phase....

HugeGraph is a convenient, efficient, and adaptable graph database compatible with the Apache TinkerPop3 framework and the Gremlin query language. HugeGraph supports fast import performance in the case of more than 10 billion Vertices and Edges Graph, millisecond-level OLTP query capability, and can be integrated into big data platforms like Hadoop or Spark for OLAP analysis. The main scenarios of HugeGraph include correlation search, fraud detection, and knowledge graph. Not only supports...

.NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. This means you can use .NET for Apache Spark anywhere you write...

How to extract meaningful information from big data has been a popular open problem. Decision tree, which has a high degree of knowledge interpretation, has been favored in many real world applications. However noisy values commonly exist in high-speed data streams, e.g. real-time online data feeds that are prone to interference. When processing big data, it is hard to implement pre-processing and sampling in full batches. To solve this trade-off, we propose a new decision tree so called...