-
公开(公告)号：US10055403B2
公开(公告)日：2018-08-21
申请号：US15017305
申请日：2016-02-05
发明人： Trung Huu Bui , Hung Hai Bui , Franck Dernoncourt
CPC分类号： G06F17/279 , G06F17/277 , G06F17/2795 , G10L15/22
摘要： The present disclosure relates dialog states, which computers use to internally represent what users have in mind in dialog. A dialog state tracker employs various rules that enhance the ability of computers to correctly identify the presence of slot-value pairs, which make up dialog states, in utterances or conversational input of dialog. Some rules provide for identifying synonyms of values of slot-values pairs in utterances. Other rules provide for identifying slot-value pairs based on coreferences between utterances and previous utterances of dialog sessions. Rules are also provided for carrying over slot-value pairs from dialog states of previous utterances to a dialog state of a current utterance. Yet other rules provide for removing slot-value pairs from candidate dialog states, which are later used as dialog states of utterances.
-
2.发明申请公开(公告)号：US20180373952A1
公开(公告)日：2018-12-27
申请号：US15630779
申请日：2017-06-22
发明人： Trung Huu Bui , Hung Hai Bui , Shawn Alan Gaither , Walter Wei-Tuh Chang , Michael Frank Kraley , Pranjal Daga
摘要： The present invention is directed towards providing automated workflows for the identification of a reading order from text segments extracted from a document. Ordering the text segments is based on trained natural language models. In some embodiments, the workflows are enabled to perform a method for identifying a sequence associated with a portable document. The methods includes iteratively generating a probabilistic language model, receiving the portable document, and selectively extracting features (such as but not limited to text segments) from the document. The method may generate pairs of features (or feature pair from the extracted features). The method may further generate a score for each of the pairs based on the probabilistic language model and determine an order to features based on the scores. The method may provide the extracted features in the determined order.
-
3.发明申请公开(公告)号：US20180276691A1
公开(公告)日：2018-09-27
申请号：US15465449
申请日：2017-03-21
CPC分类号： G06Q30/0202 , G06N3/0445 , G06N3/08 , G06Q30/0205
摘要： Metric forecasting techniques and systems in a digital medium environment are described that leverage similarity of elements, one to another, in order to generate a forecast value for a metric for a particular element. In one example, training data is received that describes a time series of values of the metric for a plurality of elements. The model is trained to generate the forecast value of the metric, the training using machine learning of a neural network based on the training data. The training includes generating dimensional-transformation data configured to transform the training data into a simplified representation to determine similarity of the plurality of elements, one to another, with respect to the metric over the time series. The training also includes generating model parameters of the neural network based on the simplified representation to generate the forecast value of the metric.
-
-
搜索结果
3 条记录 (耗时 0.013 秒)
