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11.发明授权公开(公告)号：US11271820B2
公开(公告)日：2022-03-08
申请号：US16199090
申请日：2018-11-23
摘要： A graphical event model method, system, and computer program product, include learning statistical and causal co-occurrence relationships among multiple event-types of data, requiring no complex input, and generating a representation that explains a mutual dynamic of the multiple event-types in a form of a graphical event model.
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12.发明授权公开(公告)号：US10713303B2
公开(公告)日：2020-07-14
申请号：US14991117
申请日：2016-01-08
IPC分类号： G06F16/904
摘要： A system, computer program product, and method is described to provide a visualization tool which portrays the certain equivalent for one or more hypothetical (i.e. synthetic) or real probability distributions p(m), and optionally allows the user to manipulate that representation, resulting in associated changes to the underlying utility function u(m). In a first example, the risk preference visualization tool allows one to explore how the certain equivalent depends upon the probability distribution p(m), for a fixed utility function u(m). In a second example, the risk preference visualization tool allows one to explore how the certain equivalent depends upon the utility function u(m), assuming one or more fixed probability distributions p1(m), p2 (m), etc. In a third example, the decision maker can provide feedback through the visualization tool that would cause their utility function to be modified.
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13.发明授权公开(公告)号：US10467638B2
公开(公告)日：2019-11-05
申请号：US14459848
申请日：2014-08-14
IPC分类号： G06Q30/02
摘要： A method includes predicting availability of a plurality of constituents for one or more future epochs, obtaining one or more metrics for each of a plurality of existing work products, each of the plurality of existing work products using at least one constituent, and generating at least one work product for each of the one or more future epochs based in part on the predicted availability of the constituents and the one or more metrics for the existing work products. The metrics for the existing work products may include quality metrics and novelty metrics.
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公开(公告)号：US20190197446A1
公开(公告)日：2019-06-27
申请号：US15850100
申请日：2017-12-21
CPC分类号： G06Q10/06312 , G06F16/3344 , G06F16/335 , G06N5/02 , G06N7/005
摘要： Techniques for multi-attribute evaluation of narratives are provided. Inputs are obtained representing: (i) at least one historical dataset of events; (ii) a set of candidate narratives, wherein each candidate narrative is a potential future event sequence; and (iii) a query, wherein the query comprises one or more events of interest to a user. Attribute scores are computed for at least a subset of the candidate narratives based on at least a portion of the obtained input. One of the attribute scores comprises a plausibility attribute score representing a measure estimating the likelihood that a given candidate narrative will occur in the future. Another one of the attribute scores comprises a surprise attribute score representing a measure estimating how surprising a given candidate narrative will be to the user.
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公开(公告)号：US20180336507A1
公开(公告)日：2018-11-22
申请号：US15962213
申请日：2018-04-25
发明人： Ruben Rodriguez Torrado , Debarun Bhattacharjya , Jeffrey Owen Kephart , Jesus Maria Rios Aliaga , Dharmashankar Subramanian , Enara C. Vijil
摘要： A risk modeling system, method and program product. A query orchestrator interfaces with users posing high-level queries and expanding high-level queries into lower level queries. A queryable risk extractor applies lower level queries to available risk-related knowledge to extract potential risks, e.g., to petrochemical resource production in a selected locale. A semantic enrichment unit applies semantic enrichment to extracted potential risks and selectively annotates the enriched results. A risk model builder generates a graphical risk model for display on a display. Risk analyst can use the graphical risk model to augment risk-related intelligence.
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16.发明申请公开(公告)号：US20140200827A1
公开(公告)日：2014-07-17
申请号：US13906883
申请日：2013-05-31
发明人： Debarun Bhattacharjya , Arun Hampapur , Qing He , Hongfei Li , Dhaivat P. Parikh
IPC分类号： B61K9/08
CPC分类号： B61K9/08 , B61L23/042 , B61L27/0055 , B61L27/0088 , G06F17/5009 , G06Q10/06 , G06Q10/0635
摘要： Geo-defect repair modeling is provided. A method includes logically dividing a railroad network according to spatial and temporal dimensions with respect to historical data collected. The spatial dimensions include line segments of a specified length and the temporal dimensions include inspection run data for inspections performed for each of the line segments over a period of time. The method also includes creating a track deterioration model from the historical data, identifying geo-defects occurring at each inspection run from the track deterioration model, calculating a track deterioration condition from the track deterioration model by analyzing quantified changes in the geo-defects measured at each inspection run, and calculating a derailment risk based on track conditions determined from the inspection run data and the track deterioration condition. The method further includes determining a repair decision for each of the geo-defects based on the derailment risk and costs associated with previous comparable repairs.
摘要翻译： 提供了地质缺陷修复建模。 一种方法包括根据收集的历史数据根据空间和时间维度逻辑地划分铁路网络。 空间维度包括指定长度的线段，并且时间维度包括在一段时间内为每个线段执行检查的检查运行数据。 该方法还包括根据历史数据创建轨道退化模型，从轨道劣化模型中识别在每个检测运行中发生的地质缺陷，通过分析在轨迹退化模型中测量的地质缺陷的量化变化， 每次检查运行，并根据从检查运行数据和轨道劣化状况确定的轨道条件计算脱轨风险。 该方法还包括基于脱轨风险和与先前相似维修相关联的成本来确定每个地理缺陷的修复决策。
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公开(公告)号：US20240144058A1
公开(公告)日：2024-05-02
申请号：US18050621
申请日：2022-10-28
发明人： Radu Marinescu , HAIFENG QIAN , Debarun Bhattacharjya , Alexander Gray , Francisco Barahona , Tian GAO , Ryan Nelson Riegel
摘要： According to one embodiment, a method, computer system, and computer program product for probabilistic inference from imprecise knowledge is provided. The embodiment may include identifying a knowledge base of one or more statements and first probability distributions corresponding to each of the one or more statements. The embodiment may also include identifying one or more queries. The embodiment may further include determining logical inferences about and second probability distributions for queries from the one or more queries or statements from the one or more statements based on information in the knowledge base.
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18.发明申请公开(公告)号：US20230123421A1
公开(公告)日：2023-04-20
申请号：US17503557
申请日：2021-10-18
摘要： A computer system, computer program product, and computer-implemented method are provided that includes learning a tree ordered graphical event model from an event dataset. Temporal relationships between one or more events in received temporal event data is modeled, and an ordered graphical event model (OGEM) graph is learned. The learned OGEM graph is configured to capture ordinal historical dependence. Leveraging the learned OGEM graph, a parameter sharing architecture is learned, including order dependent statistical and causal co-occurrence relationships among event types. A control signal to an operatively coupled event device that is associated with at least one event type reflected in the learned parameter sharing environment is dynamically issued. The control signal is configured to selectively control an event injection.
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公开(公告)号：US20210383194A1
公开(公告)日：2021-12-09
申请号：US16894970
申请日：2020-06-08
摘要： A computer-implemented method is presented for learning relationships between multiple event types by employing a multi-channel neural graphical event model (MCN-GEM). The method includes receiving, by a computing device, time-stamped, asynchronous, irregularly spaced event epochs, generating, by the computing device, at least one fake epoch between each inter-event interval, wherein fake epochs represent negative evidence, feeding the event epochs and the at least one fake epoch into long short term memory (LSTM) cells, computing hidden states for each of the event epochs and the at least one fake epoch, feeding the hidden states into spatial and temporal attention models, and employing an average attention across all event epochs to generate causal graphs representing causal relationships between all the event epochs.
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公开(公告)号：US20200234163A1
公开(公告)日：2020-07-23
申请号：US16250137
申请日：2019-01-17
摘要： A method of data room content evaluation and a computer program product therefor. Valuation inputs indicate contents expected to be determined in a data room visit. A score range is selected for each valuation input and prior models are elicited. Conditional probabilities for a likelihood model are estimated interactively. Using estimated conditional probabilities the value of a visit or visits are calculated for subsequent analysis. Then, the value of data room visits may be determined by interactively analyzing estimated conditional probabilities.
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