公开(公告)号：US08965820B2

公开(公告)日：2015-02-24

申请号：US13602706

申请日：2012-09-04

申请人： Vishal Kapadia ,  John Jensen ,  Geralyn McBride ,  Jagan Sundaramoothy ,  Raghavendra Deshmukh ,  Piyush Sacheti ,  Chandrashekar Althati

发明人： Vishal Kapadia ,  John Jensen ,  Geralyn McBride ,  Jagan Sundaramoothy ,  Raghavendra Deshmukh ,  Piyush Sacheti ,  Chandrashekar Althati

IPC分类号： G06F15/18 ,  G06N5/02

CPC分类号： G06Q10/101 ,  G06F17/30598 ,  G06N5/025

摘要： Embodiments relate to classification of transactions based upon analysis of multiple variables. For a purchase transaction, such variables can include but are not limited to: buying location, source system, line of business, cost center, functional area, supplier capabilities, item description, account description, organization, department, custom parameters, and others. Embodiments may rely upon one or more classification schemes, such as statistical classification, semantic classification, and/or knowledge base classification, taken alone or in combination. In a purchase transaction, classification based on multivariate analysis facilitates identification of a purchased item or service, and hence accuracy in classifying and assigning a central classification code. Particular embodiments may include a feature allowing user review/revision of category assignments via a feedback loop linked to past classification. This revision feature may add clarity to a current transaction, allow modification of future classification for ongoing improvement, and provide a user-driven measure of system performance.

摘要翻译： 实施例涉及基于多变量分析的交易分类。 对于购买交易，这些变量可以包括但不限于：购买位置，源系统，业务线，成本中心，功能区域，供应商能力，项目描述，帐户描述，组织，部门，自定义参数等。 实施例可以依赖一个或多个分类方案，例如统计分类，语义分类和/或知识库分类，单独或组合使用。 在购买交易中，基于多变量分析的分类便于识别所购买的商品或服务，因此有助于分类和分配中央分类代码的准确性。 特定实施例可以包括允许用户通过与过去分类相关联的反馈循环来审查/修改类别分配的特征。 此修订功能可以增加当前事务的清晰度，允许修改未来的分类以进行持续改进，并提供用户驱动的系统性能测量。

公开(公告)号：US20140067803A1

公开(公告)日：2014-03-06

申请号：US13605523

申请日：2012-09-06

申请人： Vishal Kapadia ,  John Jensen ,  Geralyn McBride

发明人： Vishal Kapadia ,  John Jensen ,  Geralyn McBride

IPC分类号： G06F17/30

CPC分类号： G06F17/30011 ,  G06F17/30073 ,  G06F17/30286 ,  G06F17/30303 ,  G06F17/30489 ,  G06F17/30563 ,  G06F17/3061 ,  G06F17/30985

摘要： Embodiments relate to enrichment of a data warehouse utilizing a business compendium. Embodiments may employ a process comprising data standardization and cleansing, de-duplication of entries, and matching and enrichment, followed by manual review of an enriched record by a user. During standardization, data may be transformed into consistent content, placing correct data elements into appropriate fields, removing invalid characters, and/or standardizing names and addresses. Duplicate records are then detected and marked. During matching and enrichment, the existence of an entity (such as a supplier), may be verified by progressive matching against the business compendium. Enrichment may provide additional information regarding the entity (e.g. related to risk, diversity, and bankruptcy). The enriched record is available for manual review, allowing the user to change duplicates, matches, and parent/child linkages. Feedback from the user review may enhance accuracy of subsequent enrichment by self-learning aspects, reducing over time a need for manual review.

摘要翻译： 实施例涉及利用商业简报来丰富数据仓库。 实施例可以采用包括数据标准化和清洁，重复删除条目以及匹配和富集的过程，随后由用户手动审查丰富的记录。 在标准化期间，数据可以转换成一致的内容，将正确的数据元素放入适当的字段，删除无效字符和/或标准化名称和地址。 然后检测并标记重复的记录。 在配对和浓缩过程中，实体（如供应商）的存在可以通过与业务简介的渐进匹配来验证。 丰富可能提供有关实体的其他信息（例如与风险，多样性和破产有关）。 丰富的记录可用于手动审核，允许用户更改重复项，匹配项和父/子链接。 用户评论的反馈可以通过自学习方式提高后续浓缩的准确性，减少手动审查需求。

公开(公告)号：US09582555B2

公开(公告)日：2017-02-28

申请号：US13605523

申请日：2012-09-06

申请人： Vishal Kapadia ,  John Jensen ,  Geralyn McBride

发明人： Vishal Kapadia ,  John Jensen ,  Geralyn McBride

IPC分类号： G06F17/30

CPC分类号： G06F17/30011 ,  G06F17/30073 ,  G06F17/30286 ,  G06F17/30303 ,  G06F17/30489 ,  G06F17/30563 ,  G06F17/3061 ,  G06F17/30985

摘要： Embodiments relate to enrichment of a data warehouse utilizing a business compendium. Embodiments may employ a process comprising data standardization and cleansing, de-duplication of entries, and matching and enrichment, followed by manual review of an enriched record by a user. During standardization, data may be transformed into consistent content, placing correct data elements into appropriate fields, removing invalid characters, and/or standardizing names and addresses. Duplicate records are then detected and marked. During matching and enrichment, the existence of an entity (such as a supplier), may be verified by progressive matching against the business compendium. Enrichment may provide additional information regarding the entity (e.g. related to risk, diversity, and bankruptcy). The enriched record is available for manual review, allowing the user to change duplicates, matches, and parent/child linkages. Feedback from the user review may enhance accuracy of subsequent enrichment by self-learning aspects, reducing over time a need for manual review.

摘要翻译： 实施例涉及利用商业简报来丰富数据仓库。 实施例可以采用包括数据标准化和清洁，重复删除条目以及匹配和富集的过程，随后由用户手动审查丰富的记录。 在标准化期间，数据可以转换成一致的内容，将正确的数据元素放入适当的字段，删除无效字符和/或标准化名称和地址。 然后检测并标记重复的记录。 在配对和浓缩过程中，实体（如供应商）的存在可以通过与业务简介的渐进匹配来验证。 丰富可能提供有关实体的其他信息（例如与风险，多样性和破产有关）。 丰富的记录可用于手动审核，允许用户更改重复项，匹配项和父/子链接。 用户评论的反馈可以通过自学习方式提高后续浓缩的准确性，减少手动审查需求。

公开(公告)号：US20140067737A1

公开(公告)日：2014-03-06

申请号：US13602706

申请日：2012-09-04

申请人： Vishal Kapadia ,  John Jensen ,  Geralyn McBride ,  Jagan Sundaramoothy ,  Raghavendra Deshmukh ,  Piyush Sacheti ,  Chandrashekar Althati

发明人： Vishal Kapadia ,  John Jensen ,  Geralyn McBride ,  Jagan Sundaramoothy ,  Raghavendra Deshmukh ,  Piyush Sacheti ,  Chandrashekar Althati

IPC分类号： G06F15/18

CPC分类号： G06Q10/101 ,  G06F17/30598 ,  G06N5/025

摘要： Embodiments relate to classification of transactions based upon analysis of multiple variables. For a purchase transaction, such variables can include but are not limited to: buying location, source system, line of business, cost center, functional area, supplier capabilities, item description, account description, organization, department, custom parameters, and others. Embodiments may rely upon one or more classification schemes, such as statistical classification, semantic classification, and/or knowledge base classification, taken alone or in combination. In a purchase transaction, classification based on multivariate analysis facilitates identification of a purchased item or service, and hence accuracy in classifying and assigning a central classification code. Particular embodiments may include a feature allowing user review/revision of category assignments via a feedback loop linked to past classification. This revision feature may add clarity to a current transaction, allow modification of future classification for ongoing improvement, and provide a user-driven measure of system performance.

摘要翻译： 实施例涉及基于多变量分析的交易分类。 对于购买交易，这些变量可以包括但不限于：购买位置，源系统，业务线，成本中心，功能区域，供应商能力，项目描述，帐户描述，组织，部门，自定义参数等。 实施例可以依赖一个或多个分类方案，例如统计分类，语义分类和/或知识库分类，单独或组合使用。 在购买交易中，基于多变量分析的分类便于识别所购买的商品或服务，因此有助于分类和分配中央分类代码的准确性。 特定实施例可以包括允许用户通过与过去分类相关联的反馈循环来审查/修改类别分配的特征。 此修订功能可以增加当前事务的清晰度，允许修改未来的分类以进行持续改进，并提供用户驱动的系统性能测量。