Updated at: 2023-01-11 07:46:31
Term | Description |
Admin | The top administrator of the AnyDATA system. |
API | API is a pre-defined function that an application encapsulates its service capabilities into API and opens them to users through API gateways. API includes basic information, request paths and parameters on the front and back ends, and related protocols. |
App Developer | App developer refers to the engineer who uses AnyDATA cognitive intelligence framework to develop the cognitive intelligent application and only manages the applications developed by the cognitive service center. |
Batch Task | When a knowledge graph contains a large number of entities and relationships, it can be constructed in batches according to the user's choice during the construction process. |
Cognitive Engine | Cognitive engine refers to the capability to carry out relevant analysis and calculation based on a knowledge network and realize understanding, reasoning ,and decision making, including graph computing engine, semantic understanding engine, rule engine, reasoning engine, and SDK that provides development ability for upper-level cognitive intelligence applications. |
Common User | A kind of user permission identity. Common users can view the authorized knowledge networks and the following resources. |
Contract Model | The contract model is a model that automatically extracts contract elements based on NLP techniques. |
Data Administrator | Manage the owner permissions of all knowledge network data, that is, audit and manage the knowledge network. For the knowledge network and knowledge graph, user permissions can be assigned, and the data can only be viewed but not manipulated. |
Data Quality Score | A comprehensive indicator to evaluate the repetition rate and missing rate of the knowledge graph; Data quality score =(1- repetition rate +1- the ratio of missing values)/2. |
Data Scientists | Data scientists refer to engineers or experts who use AnyDATA cognitive intelligence framework to integrate, manage, and gain insight into global data and realize data knowledge. Data scientists can create knowledge networks and manage everything under them, including knowledge graph, cognitive engine, data source, word library, and publishing. |
Data Source Management | Data source management is the entrance to managing data sources. At present, four types of data sources such as AnyShare, Hive, MySQL, and RabbitMQ are supported in the AnyDATA system. |
Data Statistics | Data statistics show scores for each of the computational dimensions of domain IQ, including data volume and data quality. |
Display Name | It is the name displayed in the AnyDATA system. It is the display name of an entity class/relationship class in the system. |
Document Knowledge Model | Document knowledge model is a general document knowledge extraction model, which uses rule extraction and deep learning model to extract the document structure and internal knowledge, and establish the association between documents. |
Domain IQ | Domain IQ is the intelligence quotient of domain knowledge networks, which is used to measure the intelligence degree that a domain knowledge network can achieve in the application of cognitive intelligence. It is the value quantification index of domain knowledge networks. |
Entity | Entity refers to things that objectively exist and can be distinguished from each other, such as specific people, things, and objects. |
Entity Class | Entity classes are abstractions of entities at the conceptual level and are used to describe the types of entities. For example: [AISHU] is [Company], and [Company] is the entity class of [AISHU]. |
Extracting Object Properties | Extracting object properties refers to the properties of the data objects in the data source. |
Extracting Objects | Extracting objects refer to data objects from data sources, which are used to map with entity classes in the process of building knowledge graphs. |
Extracting Relational Objects | Extracting relational objects refer to the data objects that represent relationships extracted from data sources and are used to map relationships in the process of building knowledge graphs. |
Extracting Relational Objects Properties | Extracting relational object properties refer to the properties of data objects representing relationships in data sources. |
< Previous:
Next: >