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    • 37. 发明申请
    • MOBILE BASED LEXICON AND FORECASTING
    • 基于移动的LEXICON和预测
    • US20160335247A1
    • 2016-11-17
    • US15218162
    • 2016-07-25
    • INTERNATIONAL BUSINESS MACHINES CORPORATION
    • Aaron K. BaughmanBlaine H. DolphKamran R. KhanCarlos A. Paez, Jr.Palani Sakthi
    • G06F17/27G06F17/30
    • G06F17/277G06F17/2785G06F17/30654G06F17/30675G06F17/30684G06F17/30699
    • An approach is provided for ranking candidate answers to a natural language question. Candidate answers to a natural language question received from a mobile device are generated. First contextual information about a user of the mobile device is identified. A prioritization of definitions of terms is determined. Based on the prioritization, a lexicon of the terms is generated. Using mobile-based time series manipulation and pattern recognition and based on historical usage of the mobile device, a location of the user, an environment of the user, and a bodily function of the user, second contextual information is forecasted. Based on a word sense disambiguation of the terms in the lexicon and an adjustment of the prioritization, the candidate answers are modified and then ranked. The highest ranked candidate answer is more likely to be a correct answer to the natural language question than the other candidate answers.
    • 提供了一种用于对自然语言问题的候选答案进行排名的方法。 生成从移动设备接收到的自然语言问题的候选答案。 识别关于移动设备的用户的第一上下文信息。 确定术语定义的优先级。 基于优先级排序,产生词汇的词典。 使用基于移动的时间序列操作和模式识别,并且基于移动设备的历史使用,用户的位置,用户的环境以及用户的身体功能,预测第二上下文信息。 基于单词意义上的歧义,词汇中的术语和优先级的调整,候选答案被修改,然后排名。 排名最高的候选人答案更可能是对自然语言问题的正确答案,而不是其他候选人的答案。