公开(公告)号：US20120278038A1

公开(公告)日：2012-11-01

申请号：US13098076

申请日：2011-04-29

申请人： Lianjun An ,  Huijing Jiang ,  Young Min Lee ,  Fei Liu ,  Estepan Meliksetian ,  Chandrasekhara K. Reddy

发明人： Lianjun An ,  Huijing Jiang ,  Young Min Lee ,  Fei Liu ,  Estepan Meliksetian ,  Chandrasekhara K. Reddy

IPC分类号： G06F19/00

CPC分类号： G06Q10/04 ,  F24D19/1048 ,  F24D19/1063 ,  F24D19/1081 ,  G06Q50/06

摘要： Estimating monthly heating oil consumption of a building that uses heating oil and non-oil source of energy, may include separating by applying statistical models, yearly consumption of oil data associated with the building into base load oil consumption and space heating oil consumption. The separating may also include determining monthly base load oil consumption associated with the building. Monthly space heating consumption of oil may be estimated by applying a heating degree day density function to the space heating oil consumption. The monthly space heating consumption may be aggregated with the monthly base load oil consumption to estimate the monthly heating oil consumption.

摘要翻译： 估计使用取暖油和非油源能源的建筑物的每月采暖油消耗量可能包括通过应用统计模型分离，将与建筑相关的石油数据的年消耗量降低为基础油耗和空间采暖油消耗量。 分离还可以包括确定与建筑物相关联的每月基础油耗。 可以通过将加热度日密度函数应用于空间加热油消耗来估计每月空间加热消耗的油。 每月空间采暖消耗量可以与每月基本负荷油耗相结合，以估算每月采暖油消耗量。

公开(公告)号：US09031888B2

公开(公告)日：2015-05-12

申请号：US13206981

申请日：2011-08-10

申请人： Richard D. Lawrence ,  Estepan Meliksetian ,  Prem Melville ,  Claudia Perlich ,  Karthik Subbian

发明人： Richard D. Lawrence ,  Estepan Meliksetian ,  Prem Melville ,  Claudia Perlich ,  Karthik Subbian

IPC分类号： G06Q10/10 ,  G06Q50/00

CPC分类号： G06N5/04 ,  G06N99/005 ,  G06Q10/10 ,  G06Q30/0201 ,  G06Q50/01

摘要： A method, system and computer program product are disclosed for predicting influence in a social network. In one embodiment, the method comprises identifying a set of users of the social network, and identifying a subset of the users as influential users based on defined criteria. A multitude of measures are identified as predictors of which ones of the set of users are the influential users. These measures are aggregated, and a composite predictor model is formed based on this aggregation. This composite predictor model is used to predict which ones of the set of users will have a specified influence in the social network in the future. In one embodiment, the specified influence is based on messages sent from the users, and for example, may be based on the number of the messages sent from each user that are re-sent by other users.

摘要翻译： 公开了用于预测社交网络中的影响的方法，系统和计算机程序产品。 在一个实施例中，该方法包括识别社交网络的一组用户，并且基于定义的标准将用户的子集识别为有影响力的用户。 许多措施被确定为一组用户中有哪些是有影响力的用户的预测因子。 这些度量被聚合，并且基于该聚合形成复合预测器模型。 这种复合预测模型用于预测未来在社交网络中哪一组用户将具有特定的影响。 在一个实施例中，指定的影响基于从用户发送的消息，并且例如可以基于由其他用户重新发送的每个用户发送的消息的数量。

公开(公告)号：US20130041860A1

公开(公告)日：2013-02-14

申请号：US13206981

申请日：2011-08-10

申请人： Richard D. Lawrence ,  Estepan Meliksetian ,  Prem Melville ,  Claudia Perlich ,  Karthik Subbian

发明人： Richard D. Lawrence ,  Estepan Meliksetian ,  Prem Melville ,  Claudia Perlich ,  Karthik Subbian

IPC分类号： G06N5/02

CPC分类号： G06N5/04 ,  G06N99/005 ,  G06Q10/10 ,  G06Q30/0201 ,  G06Q50/01

摘要： A method, system and computer program product are disclosed for predicting influence in a social network. In one embodiment, the method comprises identifying a set of users of the social network, and identifying a subset of the users as influential users based on defined criteria. A multitude of measures are identified as predictors of which ones of the set of users are the influential users. These measures are aggregated, and a composite predictor model is formed based on this aggregation. This composite predictor model is used to predict which ones of the set of users will have a specified influence in the social network in the future. In one embodiment, the specified influence is based on messages sent from the users, and for example, may be based on the number of the messages sent from each user that are re-sent by other users.