Invention Grant
US08577829B2 Extracting information from unstructured data and mapping the information to a structured schema using the naïve bayesian probability model
有权
从非结构化数据提取信息,并使用朴实的贝叶斯概率模型将信息映射到结构化模式
- Patent Title: Extracting information from unstructured data and mapping the information to a structured schema using the naïve bayesian probability model
- Patent Title (中): 从非结构化数据提取信息,并使用朴实的贝叶斯概率模型将信息映射到结构化模式
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Application No.: US12881036Application Date: 2010-09-13
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Publication No.: US08577829B2Publication Date: 2013-11-05
- Inventor: Rajiv Subrahmanyam , Hector Aguilar-Macias
- Applicant: Rajiv Subrahmanyam , Hector Aguilar-Macias
- Applicant Address: US TN Houston
- Assignee: Hewlett-Packard Development Company, L.P.
- Current Assignee: Hewlett-Packard Development Company, L.P.
- Current Assignee Address: US TN Houston
- Main IPC: G06F17/21
- IPC: G06F17/21 ; G06F17/40

Abstract:
An “unstructured event parser” analyzes an event that is in unstructured form and generates an event that is in structured form. A mapping phase determines, for a given event token, possible fields of the structured event schema to which the token could be mapped and the probabilities that the token should be mapped to those fields. Particular tokens are then mapped to particular fields of the structured event schema. By using the Naïve Bayesian probability model, a “probabilistic mapper” determines, for a particular token and a particular field, the probability that that token maps to that field. The probabilistic mapper can also be used in a “regular expression creator” that generates a regex that matches an unstructured event and a “parameter file creator” that helps a user create a parameter file for use with a parameterized normalized event generator to generate a normalized event based on an unstructured event.
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