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System, method and application of ontology driven inferencing-based personalization systems

机译:基于本体驱动的基于推理的个性化系统的系统,方法和应用

摘要

The present invention provides a system, method, and applications for providing personalized user experiences based on the use of a core ontology and inferencing over the ontology using rules provided by a domain expert. The population of users may be known to a commerce or information service from external and internal user data sources. Information (data) about this population is brought into a knowledge warehouse designed for on-line analytic processing, and potentially data marts. Data can be sourced from external databases in batch or streaming mode and enhanced with real-time click stream events from internal observed user interactions. A reference ontology is either loaded into the system or defined via a domain expert. The ontology forms the central reference point for data enrichment and precise personalization. Characteristic data is tagged in accordance with direct reference to the nodes of the ontology and may be enhanced via inferencing techniques. This results in enriched and more precise data tagging and equates to discovery of interest domains not directly observed in the initial source data. Definitions of communities can be embedded in the reference ontology thereby allowing the rapid assignment of individuals to collaborative filters or discovered via statistical means using the enriched attributes. Discovery can be fed back into the ontology to add extensions to the ontology. The same reference ontology is used to tag content, which results in a consistent tagging discipline for data and content centered on the reference ontology. Using inference techniques based on the ontology, content may be enriched to discover attributes not explicitly announced in the content descriptions. The enriched data may be mapped to the enriched content resulting in a deeply personalized user experience.
机译:本发明提供了一种系统,方法和应用,用于基于核心本体的使用来提供个性化的用户体验,并使用领域专家提供的规则来推断本体。商业或信息服务可能会从外部和内部用户数据源获悉用户数量。有关此人口的信息(数据)被带入专为在线分析处理而设计的知识仓库以及潜在的数据集市。数据可以批处理或流模式从外部数据库中获取,并通过内部观察到的用户交互的实时点击流事件进行增强。参考本体被加载到系统中或通过领域专家定义。本体形成了数据丰富和精确个性化的中心参考点。根据直接参考本体的节点来标记特征数据,并且可以通过推理技术对其进行增强。这导致丰富和更精确的数据标记,并且等同于发现在初始源数据中未直接观察到的兴趣域。社区的定义可以嵌入到参考本体中,从而允许将个人快速分配给协作过滤器,或者使用丰富的属性通过统计手段发现。发现可以反馈到本体中,以添加本体扩展。相同的参考本体用于标记内容,这导致以参考本体为中心的数据和内容的一致标记规则。使用基于本体的推理技术,可以丰富内容以发现内容描述中未明确宣布的属性。丰富的数据可以映射到丰富的内容,从而产生深度个性化的用户体验。

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