Invention Application
- Patent Title: Extraction of Quantitative Data from Online Content
- Patent Title (中): 从在线内容中提取定量数据
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Application No.: US14594154Application Date: 2015-01-11
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Publication No.: US20160203225A1Publication Date: 2016-07-14
- Inventor: Omar Alonso , Thibault Henri Joseph Sellam
- Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC.
- Applicant Address: US WA Redmond
- Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC.
- Current Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC.
- Current Assignee Address: US WA Redmond
- Main IPC: G06F17/30
- IPC: G06F17/30

Abstract:
Systems and methods for extracting and organizing quantitative content with a corresponding topic in regard to a particular, desired event, from a body of user posts is presented. More particularly, nearly ubiquitously a body of user posts includes a substantial amount of highly relevant and interesting information goes largely unprocessed and widely inaccessible. According to the disclosed subject matter, a body/corpus of user posts is filtered according to a desired event such that those user posts relating to a desired event is identified. Additionally, the user posts are also filtered according to whether or not the user posts include a quantitative value. An analysis of the filtered user posts is conducted to extract, for qualifying user posts, a quantitative tuple comprising a quantitative value and a corresponding topic.
Public/Granted literature
- US10242107B2 Extraction of quantitative data from online content Public/Granted day:2019-03-26
Information query