发明名称 Personalized search library based on continual concept correlation
摘要 A system, devices, and methods for providing a personalized search library based on continual concept correlation include a client computing device and a personalized content server. Content events representing content accessed or manipulated by a user of the client computing device are continually generated. Content associated with the content events is continually parsed and analyzed to extract main concepts. The extracted concepts are correlated and weighted into a concept model, based on the order of the content events. The concept model parallels the structure of the user's memory. Data sources are continually searched for content relevant to a current context of the concept model. Relevant content is indexed according to the concept model. The relevant content may be made available to the user upon request or proactively. Relevant content may be cached for future use by the user. Other embodiments are described and claimed.
申请公布号 US9582572(B2) 申请公布日期 2017.02.28
申请号 US201213719563 申请日期 2012.12.19
申请人 Intel Corporation 发明人 Mo Stanley;Wouhaybi Rita H.;Mian Mubashir A.;Kohlenberg Tobias M.;Baca Jim S.
分类号 G06F17/30 主分类号 G06F17/30
代理机构 Barnes & Thornburg LLP 代理人 Barnes & Thornburg LLP
主权项 1. A computing device to provide a personalized search library based on continual concept correlation, the computing device comprising: natural language analyzer circuitry to (i) receive event data representing content accessed by a user of a client computing device, wherein an order of the event data represents an order that the user of the client computing device accessed the content and (ii) analyze the event data to extract concepts of the content; and correlation circuitry to (i) correlate the extracted concepts based on the order of the event data to generate a plurality of correlations between the extracted concepts, wherein each correlation is indicative of a relationship between a first extracted concept and a second extracted concept based on the order of the event data, (ii) adjust a weight associated with each extracted concept based on a frequency of the extracted concept occurring in the content to generate an adjusted weight, and (iii) store the correlations, adjusted weights, and extracted concepts in a concept model that identifies the relative correlation between each extracted concept and the adjusted weight associated with each extracted concept.
地址 Santa Clara CA US