今日荐股：2017年4月18日机构强烈推荐6股可闭眼买
百度 本次《实施办法》主要修改内容包括：一，根据《证券交易所管理办法》规定和监管需要，调整和完善纪律处分与监管措施种类，给交易所一线监管装上强有力的“牙齿”，例如增加对证券发行人及相关市场参与主体、会员收取惩罚性违约金、要求会员拒绝接受投资者港股通交易委托等纪律处分，增加向相关主管部门出具监管建议函等监管措施；二，优化限制交易纪律处分实施程序，提高对严重异常交易行为监管效率；三，进一步优化纪律处分和监管措施实施机制、标准和程序，例如增加从轻、减轻、从重实施纪律处分和监管措施的情形；四，扩大纪律处分听证范围，将暂停或者限制交易权限、取消交易参与人资格、取消会员资格、收取惩罚性违约金、认定为不合格投资者等纪律处分纳入听证范围。Core Structure
These are the structural linkages among the core knowledge bases for this RC: ... more
The core structure for KBpedia is derived from six (6) main knowledge bases — OpenCyc, UMBEL, GeoNames, DBpedia, Wikipedia and Wikidata. The conceptual relationships in the KBpedia Knowledge Ontology (KKO) are largely drawn from OpenCyc and UMBEL, though any of the other four sources may contribute local knowledge graph structure. Additional reference concepts (RCs) are contributed primarily from GeoNames and Wikipedia. Wikidata contributes the bulk of the instance data, though instance records are actually drawn from all sources. DBpedia and Wikidata are also the primary sources for attribute characterizations of the instances.
Two characteristics define what is a core contributor to the KBpedia structure: 1) the scale and completeness of the source; and 2) its contribution of a large number of RCs to the overall KKO knowledge graph. The KBs in the core structure play a central role in the scope and definition of KBpedia. This core structure of KBpedia is supplemented by mappings to about 20 additional external linkages, which are highly useful for interoperability purposes, but do not themselves contribute to the same extent to the RC scope of the KKO graph.
Instances (or entities) are related to the KKO graph via the rdfs:type predicate, which assigns an entity to one or more parental classes. RCs within the KKO graph may be equivalent (owl:equivalentClass), a parent super class (kko:superClassOf), a child sub class (rdfs:subClassOf), or a closely related concept (kko:isCloselyRelated). These relationships define the edges between the nodes in the graph structure, and are also the basis for logical inferencing.
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External Linkages
The LightBulb-Incandescent concept has these mappings to external knowledge graphs: ... more
KBpedia reference concepts (RCs) are linked to thousands of classes defined in nearly 20 external ontologies used to describe all kinds of public and private datasets. Some of the prominent external vocabularies include schema.org, the major structured data system for search engines, and Dublin Core, a key vocabulary from the library community. Other external vocabularies cover music, organizations, projects, social media, and the like.
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Typologies
The LightBulb-Incandescent concept is a member of these typologies: ... more
About 3/4 of all of the reference concepts (RCs) in KBpedia represent classes of entities, which themselves are organized into about 30 typologies. Most of these typologies are disjoint (lack overlap) from one another, which provides an efficient mechanism for testing subsets and filtering entities into smaller groups for computational purposes.
The major groupings of types reside in core typologies, which is where the largest degree of disjointedness occurs. There are some upper typologies (such as Living Things over Plants, Animals, etc.) that are used mostly for organizational purposes. The core typologies are the key ones to focus upon for distinguishing large groupings of entities.
Broader Concepts
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Broader concepts represent the parents (or grandparental lineage in the case of inference) for the current reference concept (RC). The broader concept relationship is expressed using the transitive kko:superClassOf property. This property is the inverse of the rdfs:subClassOf property.
Narrower Concepts
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Narrower concepts represent the children (or grandchild lineages in the case of inference) for the current reference concept (RC). The narrower concept relationship is expressed using the transitive rdfs:subClassOf property. This property is the inverse of the kko:superClassOf property.
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KBpedia exploits large-scale knowledge bases and semantic technologies for machine learning, data interoperability and mapping, and fact extraction and tagging.
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- KBpedia Adds Major eCommerce Capabilities 06/15/2020
- KBpedia Continues Quality Improvements 12/04/2019
- Wikidata Coverage Nearly Complete (98%) 04/08/2019
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