公开(公告)号：US08650075B2

公开(公告)日：2014-02-11

申请号：US13332590

申请日：2011-12-21

申请人： Andrew E. Fano ,  Chad M. Cumby ,  Rayid Ghani ,  Marko Krema

发明人： Andrew E. Fano ,  Chad M. Cumby ,  Rayid Ghani ,  Marko Krema

IPC分类号： G06Q30/00

CPC分类号： G06Q30/0202 ,  G06N99/005 ,  G06Q10/087 ,  G06Q30/02 ,  G06Q30/0207 ,  G06Q30/0224 ,  G06Q30/0226 ,  G06Q30/0242 ,  G06Q30/0245 ,  G06Q30/0255 ,  G06Q30/0269 ,  G06Q30/0273 ,  G06Q30/0631 ,  G06Q30/0633 ,  G06Q50/12

摘要： A method and system for using individualized customer models when operating a retail establishment is provided. The individualized customer models may be generated using statistical analysis of transaction data for the customer, thereby generating sub-models and attributes tailored to customer. The individualized customer models may be used in any aspect of a retail establishment's operations, ranging from supply chain management issues, inventory control, promotion planning (such as selecting parameters for a promotion or simulating results of a promotion), to customer interaction (such as providing a shopping list or providing individualized promotions).

公开(公告)号：US20130054502A1

公开(公告)日：2013-02-28

申请号：US13221592

申请日：2011-08-30

申请人： Andrew E. Fano ,  Chad Cumby ,  Marko Krema ,  Sai P. Kandallu

发明人： Andrew E. Fano ,  Chad Cumby ,  Marko Krema ,  Sai P. Kandallu

IPC分类号： G06N5/02

CPC分类号： G06N5/02 ,  G06F17/30554

摘要： A plurality of topics encompassed in a document are determined and, for each such topic, a sentiment for that topic is likewise determined. Thereafter, credibility of the document is determined based on the resulting plurality of sentiments. In one embodiment, credibility of at least one target document is established by first determining, for each of a plurality of portions of the at least one target document, at least one topic encompassed in the portion to provide a plurality of target topics. Likewise, sentiment scores are determined for each portion. Thereafter, for each prior topic of a plurality of prior topics, a topic-sentiment score is determined based on sentiment scores corresponding to those portions of the plurality of portions having a target topic corresponding to the prior topic. A credibility index is determined based on the resulting plurality of topic-sentiment scores.

摘要翻译： 确定文档中包含的多个主题，并且对于每个这样的主题，同样确定该主题的情绪。 此后，基于所得到的多个情绪来确定文档的可信度。 在一个实施例中，通过首先针对至少一个目标文档的多个部分中的每一个来确定包含在该部分中以提供多个目标主题的至少一个主题来建立至少一个目标文档的可信度。 同样，每个部分都确定情绪评分。 此后，对于多个先前主题的每个先前的主题，基于与具有与先前主题相对应的目标主题的多个部分的那些部分相对应的情感评分来确定话题情绪评分。 基于所得到的多个主题情绪评分来确定可信性指数。

公开(公告)号：US20130018825A1

公开(公告)日：2013-01-17

申请号：US13179741

申请日：2011-07-11

申请人： Rayid GHANI ,  Marko Krema

发明人： Rayid GHANI ,  Marko Krema

IPC分类号： G06F15/18

CPC分类号： G06N99/005

摘要： In a machine learning system in which a plurality of learned models, each corresponding to a unique domain, already exist, new domain input for training a new domain model may be provided. Statistical characteristics of features in the new domain input are first determined. The resulting new domain statistical characteristics are then compared with statistical characteristics of features in prior input previously provided for training at least some of the plurality of learned models. Thereafter, at least one learned model of the plurality of learned models is identified as the basis for the new domain model when the new domain input statistical characteristics compare favorably with the statistical characteristics of the features in the prior input corresponding to the at least one learned model.

摘要翻译： 在其中存在多个学习模型（每个对应于唯一域）的机器学习系统中，可以提供用于训练新域模型的新域输入。 首先确定新域输入中特征的统计特征。 然后将所得到的新的域统计特征与先前提供用于训练多个学习模型中的至少一些的先前输入中的特征的统计特征进行比较。 此后，当新的域输入统计特性与先前输入中对应于至少一个学习的特征的统计特征相比较时，多个学习模型的至少一个学习模型被识别为新域模型的基础 模型。

公开(公告)号：US07996440B2

公开(公告)日：2011-08-09

申请号：US11742215

申请日：2007-04-30

申请人： Katharina Probst ,  Rayid Ghani ,  Andrew E. Fano ,  Marko Krema ,  Yan Liu

发明人： Katharina Probst ,  Rayid Ghani ,  Andrew E. Fano ,  Marko Krema ,  Yan Liu

IPC分类号： G06F17/30

CPC分类号： G06F17/27 ,  G06F17/2745

摘要： One or more classification algorithms are applied to at least one natural language document in order to extract both attributes and values of a given product. Supervised classification algorithms, semi-supervised classification algorithms, unsupervised classification algorithms or combinations of such classification algorithms may be employed for this purpose. The at least one natural language document may be obtained via a public communication network. Two or more attributes (or two or more values) thus identified may be merged to form one or more attribute phrases or value phrases. Once attributes and values have been extracted in this manner, association or linking operations may be performed to establish attribute-value pairs that are descriptive of the product. In a presently preferred embodiment, an (unsupervised) algorithm is used to generate seed attributes and values which can then support a supervised or semi-supervised classification algorithm.

摘要翻译： 一个或多个分类算法被应用于至少一个自然语言文档，以便提取给定产品的属性和值。 为此，可以采用监督分类算法，半监督分类算法，无监督分类算法或这种分类算法的组合。 可以经由公共通信网络获得至少一个自然语言文档。 如此识别的两个或多个属性（或两个或多个值）可以被合并以形成一个或多个属性短语或值短语。 一旦以这种方式提取了属性和值，就可以执行关联或链接操作来建立描述产品的属性值对。 在当前优选的实施例中，（无监督）算法用于生成种子属性和值，然后可以支持受监督或半监督分类算法。

公开(公告)号：US07970767B2

公开(公告)日：2011-06-28

申请号：US11742244

申请日：2007-04-30

申请人： Katharina Probst ,  Rayid Ghani ,  Andrew E. Fano ,  Marko Krema ,  Yan Liu

发明人： Katharina Probst ,  Rayid Ghani ,  Andrew E. Fano ,  Marko Krema ,  Yan Liu

IPC分类号： G06F17/30

CPC分类号： G06F17/2715 ,  G06F17/241 ,  G06F17/30616

摘要： One or more classification algorithms are applied to at least one natural language document in order to extract both attributes and values of a given product. Supervised classification algorithms, semi-supervised classification algorithms, unsupervised classification algorithms or combinations of such classification algorithms may be employed for this purpose. The at least one natural language document may be obtained via a public communication network. Two or more attributes (or two or more values) thus identified may be merged to form one or more attribute phrases or value phrases. Once attributes and values have been extracted in this manner, association or linking operations may be performed to establish attribute-value pairs that are descriptive of the product. In a presently preferred embodiment, an (unsupervised) algorithm is used to generate seed attributes and values which can then support a supervised or semi-supervised classification algorithm.

公开(公告)号：US20050189414A1

公开(公告)日：2005-09-01

申请号：US11069113

申请日：2005-02-28

申请人： Andrew Fano ,  Chad Cumby ,  Rayid Ghani ,  Marko Krema

发明人： Andrew Fano ,  Chad Cumby ,  Rayid Ghani ,  Marko Krema

IPC分类号： G06K15/00 ,  G06F17/60

CPC分类号： G06Q30/02 ,  G06Q30/0226 ,  G06Q30/0245 ,  G06Q30/0247 ,  G06Q30/0255 ,  G06Q30/0273

摘要： A method and system for using individualized customer models when operating a retail establishment is provided. The individualized customer models may be generated using statistical analysis of transaction data for the customer, thereby generating sub-models and attributes tailored to customer. The individualized customer models may be used in any aspect of a retail establishment's operations, ranging from supply chain management issues, inventory control, promotion planning (such as selecting parameters for a promotion or simulating results of a promotion), to customer interaction (such as providing a shopping list or providing individualized promotions).

摘要翻译： 提供了一种在运营零售店时使用个性化客户模型的方法和系统。 可以使用对客户的交易数据的统计分析来生成个性化客户模型，从而生成针对客户量身定制的子模型和属性。 个性化的客户模型可以用于零售企业运营的任何方面，从供应链管理问题，库存控制，促销计划（如选择促销的参数或模拟促销结果）到客户交互（如 提供购物清单或提供个性化促销）。

公开(公告)号：US08676730B2

公开(公告)日：2014-03-18

申请号：US13179707

申请日：2011-07-11

申请人： Rayid Ghani ,  Marko Krema

发明人： Rayid Ghani ,  Marko Krema

IPC分类号： G06F15/18

CPC分类号： G06N99/005

摘要： Method and apparatus are provided for providing one or more sentiment classifiers from training data using supervised classification techniques based on features extracted from the training data. Training data includes a plurality of units such as, but not limited to, documents, paragraphs, sentences, and clauses. A feature extraction component extracts a plurality of features from the training data, and a feature value determination component determines a value for each extracted feature based on a frequency at which each feature occurs in the training data. On the other hand, a class labeling component labels each unit of the training data according to a plurality of sentiment classes to provide labeled training data. Thereafter, a sentiment classifier generation component provides a least one sentiment classifier based on the value of each extracted feature and the labeled training data using a supervised classification technique.

摘要翻译： 提供方法和装置，用于基于从训练数据提取的特征，使用监督分类技术从训练数据提供一个或多个情绪分类器。 训练数据包括多个单位，例如但不限于文件，段落，句子和子句。 特征提取组件从训练数据中提取多个特征，并且特征值确定组件基于每个特征在训练数据中出现的频率来确定每个提取的特征的值。 另一方面，类别标注组件根据多个情绪类标示训练数据的每个单元，以提供标记的训练数据。 此后，情绪分类器生成组件使用监督分类技术，基于每个提取的特征的值和标记的训练数据提供至少一个情感分类器。

公开(公告)号：US08645200B2

公开(公告)日：2014-02-04

申请号：US13099424

申请日：2011-05-03

申请人： Andrew E. Fano ,  Chad M. Cumby ,  Rayid Ghani ,  Marko Krema

发明人： Andrew E. Fano ,  Chad M. Cumby ,  Rayid Ghani ,  Marko Krema

IPC分类号： G06Q30/00

CPC分类号： G06Q30/0202 ,  G06N99/005 ,  G06Q10/087 ,  G06Q30/02 ,  G06Q30/0207 ,  G06Q30/0224 ,  G06Q30/0226 ,  G06Q30/0242 ,  G06Q30/0245 ,  G06Q30/0255 ,  G06Q30/0269 ,  G06Q30/0273 ,  G06Q30/0631 ,  G06Q30/0633 ,  G06Q50/12

摘要： A method and system for using individualized customer models when operating a retail establishment is provided. The individualized customer models may be generated using statistical analysis of transaction data for the customer, thereby generating sub-models and attributes tailored to customer. The individualized customer models may be used in any aspect of a retail establishment's operations, ranging from supply chain management issues, inventory control, promotion planning (such as selecting parameters for a promotion or simulating results of a promotion), to customer interaction (such as providing a shopping list or providing individualized promotions).

摘要翻译： 提供了一种在运营零售店时使用个性化客户模型的方法和系统。 可以使用对客户的交易数据的统计分析来生成个性化客户模型，从而生成针对客户量身定制的子模型和属性。 个性化的客户模型可以用于零售企业运营的任何方面，从供应链管理问题，库存控制，促销计划（如选择促销的参数或模拟促销结果）到客户交互（如 提供购物清单或提供个性化促销）。

公开(公告)号：US08521745B2

公开(公告)日：2013-08-27

申请号：US13158678

申请日：2011-06-13

申请人： Katharina Probst ,  Rayid Ghani ,  Andrew E. Fano ,  Marko Krema ,  Yan Liu

发明人： Katharina Probst ,  Rayid Ghani ,  Andrew E. Fano ,  Marko Krema ,  Yan Liu

IPC分类号： G06F17/30

CPC分类号： G06F17/2715 ,  G06F17/241 ,  G06F17/30616

摘要： One or more classification algorithms are applied to at least one natural language document in order to extract both attributes and values of a given product. Supervised classification algorithms, semi-supervised classification algorithms, unsupervised classification algorithms or combinations of such classification algorithms may be employed for this purpose. The at least one natural language document may be obtained via a public communication network. Two or more attributes (or two or more values) thus identified may be merged to form one or more attribute phrases or value phrases. Once attributes and values have been extracted in this manner, association or linking operations may be performed to establish attribute-value pairs that are descriptive of the product. In a presently preferred embodiment, an (unsupervised) algorithm is used to generate seed attributes and values which can then support a supervised or semi-supervised classification algorithm.

摘要翻译： 一个或多个分类算法被应用于至少一个自然语言文档，以便提取给定产品的属性和值。 为此，可以采用监督分类算法，半监督分类算法，无监督分类算法或这种分类算法的组合。 可以经由公共通信网络获得至少一个自然语言文档。 如此识别的两个或多个属性（或两个或多个值）可以被合并以形成一个或多个属性短语或值短语。 一旦以这种方式提取了属性和值，就可以执行关联或链接操作来建立描述产品的属性值对。 在当前优选的实施例中，（无监督）算法用于生成种子属性和值，然后可以支持受监督或半监督分类算法。

公开(公告)号：US20130018651A1

公开(公告)日：2013-01-17

申请号：US13545363

申请日：2012-07-10

申请人： Divna Djordjevic ,  Rayid Ghani ,  Marko Krema

发明人： Divna Djordjevic ,  Rayid Ghani ,  Marko Krema

IPC分类号： G06F17/27

CPC分类号： G06F17/2765 ,  G06Q10/00

摘要： A generative model is used to develop at least one topic model and at least one sentiment model for a body of text. The at least one topic model is displayed such that, in response, a user may provide user input indicating modifications to the at least one topic model. Based on the received user input, the generative model is used to provide at least one updated topic model and at least one updated sentiment model based on the user input. Thereafter, the at least one updated topic model may again be displayed in order to solicit further user input, which further input is then used to once again update the models. The at least one updated topic model and the at least one updated sentiment model may be employed to analyze target text in order to identify topics and associated sentiments therein.

摘要翻译： 生成模型用于开发至少一个主题模型和至少一个文本主体的情绪模型。 显示至少一个主题模型，使得作为响应，用户可以提供指示对至少一个主题模型的修改的用户输入。 基于所接收的用户输入，生成模型用于基于用户输入提供至少一个更新的主题模型和至少一个更新的情绪模型。 此后，可以再次显示至少一个更新的主题模型以便进一步用户输入，然后进一步输入再次更新模型。 可以使用至少一个更新的主题模型和至少一个更新的情绪模型来分析目标文本，以便识别其中的主题和相关联的情绪。