-
公开(公告)号：US20130018828A1
公开(公告)日：2013-01-17
申请号：US13619059
申请日：2012-09-14
CPC分类号： G06N5/022 , G06F16/353 , G06F16/367
摘要： A first mapping function automatically maps a plurality of documents each with a concept of ontology to create a documents-to-ontology distribution. An ontology-to-class distribution that maps concepts in the ontology to class labels, respectively, is received, and a classifier is generated that labels a selected document with an associated class identified based on the documents-to-ontology distribution and the ontology-to-class distribution.
-
2.发明申请SYSTEM AND METHOD FOR AUTOMATED LABELING OF TEXT DOCUMENTS USING ONTOLOGIES 审中-公开使用本体论自动标记文本文件的系统和方法公开(公告)号：US20130018827A1
公开(公告)日：2013-01-17
申请号：US13184156
申请日：2011-07-15
CPC分类号： G06N5/022 , G06F16/353 , G06F16/367
摘要： A first mapping function automatically maps a plurality of documents each with a concept of ontology to create a documents-to-ontology distribution. An ontology-to-class distribution that maps concepts in the ontology to class labels, respectively, is received, and a classifier is generated that labels a selected document with an associated class identified based on the documents-to-ontology distribution and the ontology-to-class distribution.
摘要翻译： 第一映射函数自动地将多个文档映射到本体的概念上以创建文档到本体分布。 接收将本体中的概念分别映射到类标签的本体到类的分发，并且生成一个分类器，该分类器将所选择的文档标记为基于文档到本体分布和本体 - 班级分配。
-
公开(公告)号：US20130151520A1
公开(公告)日：2013-06-13
申请号：US13315798
申请日：2011-12-09
申请人： Saha Ankan , Arindam Banerjee , Shiva P. Kasiviswanathan , Richard D. Lawrence , Prem Melville , Vikas Sindhwani , Edison L. Ting
发明人： Saha Ankan , Arindam Banerjee , Shiva P. Kasiviswanathan , Richard D. Lawrence , Prem Melville , Vikas Sindhwani , Edison L. Ting
IPC分类号： G06F17/30
CPC分类号： G06F17/2785 , G06F17/30619
摘要： A method, system and computer program product for inferring topic evolution and emergence in a set of documents. In one embodiment, the method comprises forming a group of matrices using text in the documents, and analyzing these matrices to identify a first group of topics as evolving topics and a second group of topics as emerging topics. The matrices includes a first matrix X identifying a multitude of words in each of the documents, a second matrix W identifying a multitude of topics in each of the documents, and a third matrix H identifying a multitude of words for each of the multitude of topics. These matrices are analyzed to identify the evolving and emerging topics. In an embodiment, the documents form a streaming dataset, and two forms of temporal regularizers are used to help identify the evolving topics and the emerging topics in the streaming dataset.
摘要翻译： 一套用于推断主题演变和出现在一组文件中的方法，系统和计算机程序产品。 在一个实施例中，该方法包括使用文档中的文本形成一组矩阵，并且分析这些矩阵以将第一组主题识别为演变主题，将第二组主题识别为新兴主题。 矩阵包括识别每个文档中的多个单词的第一矩阵X，标识每个文档中的众多主题的第二矩阵W，以及为每个主题中的每一个标识多个单词的第三矩阵H 。 对这些矩阵进行分析，以确定不断发展的新兴主题。 在一个实施例中，文档形成流数据集，并且使用两种形式的时间规则化器来帮助识别流数据集中不断发展的主题和新兴主题。
-
公开(公告)号：US20130151525A1
公开(公告)日：2013-06-13
申请号：US13616403
申请日：2012-09-14
申请人： Saha Ankan , Arindam Banerjee , Shiva P. Kasiviswanathan , Richard D. Lawrence , Prem Melville , Vikas Sindhwani , Edison L. Ting
发明人： Saha Ankan , Arindam Banerjee , Shiva P. Kasiviswanathan , Richard D. Lawrence , Prem Melville , Vikas Sindhwani , Edison L. Ting
IPC分类号： G06F17/30
CPC分类号： G06F17/2785 , G06F16/316
摘要： A method, system and computer program product for inferring topic evolution and emergence in a set of documents. In one embodiment, the method comprises forming a group of matrices using text in the documents, and analyzing these matrices to identify evolving topics and emerging topics. The matrices includes a matrix X identifying a multitude of words in each of the documents, a matrix W identifying a multitude of topics in each of the documents, and a matrix H identifying a multitude of words for each of the multitude of topics. These matrices are analyzed to identify the evolving and emerging topics. In an embodiment, two forms of temporal regularizers are used to help identify the evolving and emerging topics. In another embodiment, a two stage approach involving detection and clustering is used to help identify the evolving and emerging topics.
摘要翻译： 一套用于推断主题演变和出现在一组文件中的方法，系统和计算机程序产品。 在一个实施例中，该方法包括使用文档中的文本形成一组矩阵，并且分析这些矩阵以识别演进主题和新兴主题。 矩阵包括识别每个文档中的多个单词的矩阵X，标识每个文档中的众多主题的矩阵W以及为每个主题识别多个单词的矩阵H。 对这些矩阵进行分析，以确定不断发展的新兴主题。 在一个实施例中，使用两种形式的时间正则化器来帮助识别不断发展和新兴的主题。 在另一个实施例中，使用涉及检测和聚类的两阶段方法来帮助识别不断发展和新兴的主题。
-
公开(公告)号：US08909643B2
公开(公告)日：2014-12-09
申请号：US13315798
申请日：2011-12-09
申请人： Saha Ankan , Arindam Banerjee , Shiva P. Kasiviswanathan , Richard D. Lawrence , Prem Melville , Vikas Sindhwani , Edison L. Ting
发明人： Saha Ankan , Arindam Banerjee , Shiva P. Kasiviswanathan , Richard D. Lawrence , Prem Melville , Vikas Sindhwani , Edison L. Ting
IPC分类号： G06F17/30
CPC分类号： G06F17/2785 , G06F17/30619
摘要： A method, system and computer program product for inferring topic evolution and emergence in a set of documents. In one embodiment, the method comprises forming a group of matrices using text in the documents, and analyzing these matrices to identify a first group of topics as evolving topics and a second group of topics as emerging topics. The matrices includes a first matrix X identifying a multitude of words in each of the documents, a second matrix W identifying a multitude of topics in each of the documents, and a third matrix H identifying a multitude of words for each of the multitude of topics. These matrices are analyzed to identify the evolving and emerging topics. In an embodiment, the documents form a streaming dataset, and two forms of temporal regularizers are used to help identify the evolving topics and the emerging topics in the streaming dataset.
摘要翻译： 一套用于推断主题演变和出现在一组文件中的方法，系统和计算机程序产品。 在一个实施例中，该方法包括使用文档中的文本形成一组矩阵，并且分析这些矩阵以将第一组主题识别为演变主题，将第二组主题识别为新兴主题。 矩阵包括识别每个文档中的多个单词的第一矩阵X，标识每个文档中的众多主题的第二矩阵W，以及为每个主题中的每一个标识多个单词的第三矩阵H 。 对这些矩阵进行分析，以确定不断发展的新兴主题。 在一个实施例中，文档形成流数据集，并且使用两种形式的时间规则化器来帮助识别流数据集中不断发展的主题和新兴主题。
-
公开(公告)号：US20120143796A1
公开(公告)日：2012-06-07
申请号：US12960131
申请日：2010-12-03
申请人： Aurelie C. Lozano , Vikas Sindhwani
发明人： Aurelie C. Lozano , Vikas Sindhwani
IPC分类号： G06F15/18
CPC分类号： G06F17/18
摘要： In response to issues of high dimensionality and sparsity in machine learning, it is proposed to use a multiple output regression modeling module that takes into account information on groups of related predictor features and groups of related regressions, both given as input, and outputs a regression model with selected feature groups. Optionally, the method can be employed as a component in methods of causal influence detection, which are applied on a time series training data set representing the time-evolving content generated by community members, output a model of causal relationships and a ranking of the members according to their influence.
摘要翻译： 针对机器学习中高维度和稀疏性的问题，提出使用多输出回归建模模块，其考虑了相关预测因子组和相关回归组的信息，两者作为输入，并输出回归 型号与选定的功能组。 可选择地，该方法可以用作因果影响检测方法中的一个组件，其应用于代表由社区成员产生的时间演化内容的时间序列训练数据集，输出因果关系模型和成员的排名 根据他们的影响。
-
公开(公告)号：US08266098B2
公开(公告)日：2012-09-11
申请号：US12621285
申请日：2009-11-18
IPC分类号： G06F17/30
CPC分类号： G06Q10/00
摘要： In a computerized social network, expert and user chat sessions are stored and rated probabilistically. Later user requests for information are met with an expert ranking, based on a balance of similarities between expert profile and questions; similarity between expert profile and prior chat sessions, and dynamically updated chat session ratings. New sessions can be rated automatically with reference to keywords distilled from past sessions responsive to user ratings—and based on session length.
摘要翻译： 在电脑社交网络中，专家和用户聊天会话被概括地存储和评估。 基于专家简介和问题之间的相似性的平衡，后来的用户信息请求符合专家排名; 专家简介和以前的聊天会话之间的相似性，以及动态更新的聊天会话等级。 参考根据用户评分从过去会话中提取的关键字，并根据会话长度自动评估新会话。
-
8.发明授权Systems and methods for processing machine learning algorithms in a MapReduce environment 失效在MapReduce环境中处理机器学习算法的系统和方法公开(公告)号：US08612368B2
公开(公告)日：2013-12-17
申请号：US13038086
申请日：2011-03-01
申请人： Douglas Ronald Burdick , Amol Ghoting , Rajasekar Krishnamurthy , Edwin Peter Dawson Pednault , Berthold Reinwald , Vikas Sindhwani , Shirish Tatikonda , Yuanyuan Tian , Shivakumar Vaithyanathan
发明人： Douglas Ronald Burdick , Amol Ghoting , Rajasekar Krishnamurthy , Edwin Peter Dawson Pednault , Berthold Reinwald , Vikas Sindhwani , Shirish Tatikonda , Yuanyuan Tian , Shivakumar Vaithyanathan
IPC分类号： G06F15/18
CPC分类号： G06F9/4843 , G06F8/427
摘要： Systems and methods for processing Machine Learning (ML) algorithms in a MapReduce environment are described. In one embodiment of a method, the method includes receiving a ML algorithm to be executed in the MapReduce environment. The method further includes parsing the ML algorithm into a plurality of statement blocks in a sequence, wherein each statement block comprises a plurality of basic operations (hops). The method also includes automatically determining an execution plan for each statement block, wherein at least one of the execution plans comprises one or more low-level operations (lops). The method further includes implementing the execution plans in the sequence of the plurality of the statement blocks.
摘要翻译： 描述了MapReduce环境中处理机器学习（ML）算法的系统和方法。 在一种方法的一个实施例中，该方法包括接收要在MapReduce环境中执行的ML算法。 该方法还包括将ML算法解析为序列中的多个语句块，其中每个语句块包括多个基本操作（跳）。 该方法还包括自动确定每个语句块的执行计划，其中至少一个执行计划包括一个或多个低级操作（lops）。 该方法还包括以多个语句块的顺序来实现执行计划。
-
9.发明申请ENTERPRISE-TO-MARKET NETWORK ANALYSIS FOR SALES ENABLEMENT AND RELATIONSHIP BUILDING 审中-公开企业对市场网络分析销售和关系建设公开(公告)号：US20120046992A1
公开(公告)日：2012-02-23
申请号：US12861168
申请日：2010-08-23
摘要： There are provided a system, a method and a computer program product for increasing of productivity of sales force in a first entity. The system locates or constructs at least one enterprise social network in the first entity. The system constructs at least one market social network. The system creates at least one connection between the enterprise social network and the market social network. Sales representative in the first entity expands new sales operations and/or identify new markets via the connected social networks.
摘要翻译： 提供了一种用于在第一实体中提高销售力的生产力的系统，方法和计算机程序产品。 该系统在第一实体中定位或构建至少一个企业社交网络。 该系统构建至少一个市场社交网络。 该系统在企业社交网络和市场社会网络之间创建至少一个连接。 第一实体的销售代表通过相连的社交网络拓展新的销售业务和/或识别新市场。
-
10.发明申请公开(公告)号：US20120030020A1
公开(公告)日：2012-02-02
申请号：US12848602
申请日：2010-08-02
IPC分类号： G06Q30/00
CPC分类号： G06Q30/02 , G06Q30/0255
摘要： A system, method and computer program product automatically present at least one product to at least one client for at least one possible purchase. The system applies a matrix factorization on a binary matrix X representing which clients purchased which products. The system optimizes zero-valued elements in the matrix X that correspond to unknown client-product affinities. The system constructs based on the optimization, a prediction matrix {circumflex over (X)} whose each element value represents a likelihood that a corresponding client purchases a corresponding product. The system identifies at least one client-product pair with the highest value in the matrix {circumflex over (X)}. The system recommends at least one product to at least one client according to the client-product pair with the highest value.
摘要翻译： 系统，方法和计算机程序产品自动向至少一个客户端呈现至少一个可能的购买的至少一个产品。 系统对二进制矩阵X应用矩阵分解，表示哪些客户购买了哪些产品。 系统优化矩阵X中对应于未知客户端产品亲和度的零值元素。 该系统基于优化构建一个预测矩阵{（x）}，其每个元素值表示对应的客户端购买相应产品的可能性。 系统识别至少一个客户端 - 产品对，其矩阵中的值最大（在（X）}中。 系统根据具有最高价值的客户端 - 产品对，至少向一个客户端推荐一个产品。
-
-
-
-
-
-
-
-
-
搜索结果
19 条记录 (耗时 0.029 秒)
