公开(公告)号：US08645193B2

公开(公告)日：2014-02-04

申请号：US13554743

申请日：2012-07-20

Applicant: Michael Swinson ,  Isaac Lemon Laughlin ,  Meghashyam Grama Ramanuja ,  Mikhail Semeniuk ,  Xingchu Liu

Inventor： Michael Swinson ,  Isaac Lemon Laughlin ,  Meghashyam Grama Ramanuja ,  Mikhail Semeniuk ,  Xingchu Liu

IPC: G06Q30/00

CPC classification number: G06Q30/0278 ,  G06Q10/06 ,  G06Q30/02 ,  G06Q30/0206

Abstract: Systems and methods for the aggregation, analysis, and display of data for used vehicles are disclosed. Historical transaction data for used vehicles may be obtained and processed to determine pricing data, where this determined pricing data may be associated with a particular configuration of a vehicle. The user can then be presented with an interface pertinent to the vehicle configuration utilizing the aggregated data set or the associated determined data where the user can make a variety of determinations. This interface may, for example, be configured to present the historical transaction data visually, with the pricing data such as a trade-in price, a list price, an expected sale price or range of sale prices, market low sale price, market average sale price, market high sale price, etc. presented relative to the historical transaction data.

Abstract translation: 公开了用于二手车辆的数据的聚集，分析和显示的系统和方法。 可以获得并处理用于二手车辆的历史交易数据以确定定价数据，其中该确定的定价数据可以与车辆的特定配置相关联。 然后可以使用利用聚合数据集或用户可进行各种确定的相关联的确定数据，向用户呈现与车辆配置相关的接口。 该接口可以例如被配置为以视觉方式呈现历史交易数据，其中定价数据例如交易价格，清单价格，预期销售价格或销售价格范围，市场低售价，市场平均值 销售价格，市场销售价格等相对于历史交易数据呈现。

公开(公告)号：US09031967B2

公开(公告)日：2015-05-12

申请号：US13406325

申请日：2012-02-27

Applicant: Michael Swinson ,  Mikhail Semeniuk ,  Xingchu Liu

Inventor： Michael Swinson ,  Mikhail Semeniuk ,  Xingchu Liu

IPC: G06F17/30 ,  G06Q30/02 ,  G06F17/27

CPC classification number: G06F17/30985 ,  G06F17/2795 ,  G06F17/30684 ,  G06Q30/0283

Abstract: Natural language processing (NLP) approaches may be utilized to map two strings. The strings may come from sources utilizing different naming conventions. One example may be a data aggregator that collects used car transaction information. Another example may be a comprehensive database listing all possible manufacturer-defined vehicle options. A NLP system may operate to determine whether a source string is present in a target string and outputting a match containing the source string and the target string if the source string is present in the target string or computing a similarity factor if the source string is not present in the target string. The similarity factor representing a measure of similarity between two strings may be computed based on a plurality of parameters, including a Levenshtein edit distance parameter. The computed similarity can be used to find pricing information, including trade-in, sale, and list prices, across disparate naming conventions.

Abstract translation: 自然语言处理（NLP）方法可用于映射两个字符串。 字符串可能来自使用不同命名约定的来源。 一个示例可以是收集二手车交易信息的数据聚合器。 另一个例子可能是列出所有可能的制造商定义的车辆选项的综合数据库。 如果源字符串存在于目标字符串中，则NLP系统可以操作以确定源字符串是否存在于目标字符串中并输出包含源字符串和目标字符串的匹配，或者如果源字符串不是，则输出相似因子 存在于目标字符串中。 可以基于包括Levenshtein编辑距离参数的多个参数来计算表示两个串之间的相似度的度量的相似性因子。 计算的相似性可以用于查找不同命名约定的定价信息，包括交易，销售和列表价格。

公开(公告)号：US20130030870A1

公开(公告)日：2013-01-31

申请号：US13554743

申请日：2012-07-20

Applicant: Michael Swinson ,  Isaac Lemon Laughlin ,  Meghashyam Grama Ramanuja ,  Mikhail Semeniuk ,  Xingchu Liu

Inventor： Michael Swinson ,  Isaac Lemon Laughlin ,  Meghashyam Grama Ramanuja ,  Mikhail Semeniuk ,  Xingchu Liu

IPC: G06Q30/00

CPC classification number: G06Q30/0278 ,  G06Q10/06 ,  G06Q30/02 ,  G06Q30/0206

Abstract: Systems and methods for the aggregation, analysis, and display of data for used vehicles are disclosed. Historical transaction data for used vehicles may be obtained and processed to determine pricing data, where this determined pricing data may be associated with a particular configuration of a vehicle. The user can then be presented with an interface pertinent to the vehicle configuration utilizing the aggregated data set or the associated determined data where the user can make a variety of determinations. This interface may, for example, be configured to present the historical transaction data visually, with the pricing data such as a trade-in price, a list price, an expected sale price or range of sale prices, market low sale price, market average sale price, market high sale price, etc. presented relative to the historical transaction data.

Abstract translation: 公开了用于二手车辆的数据的聚集，分析和显示的系统和方法。 可以获得并处理用于二手车辆的历史交易数据以确定定价数据，其中该确定的定价数据可以与车辆的特定配置相关联。 然后可以使用利用聚合数据集或用户可进行各种确定的相关联的确定数据，向用户呈现与车辆配置相关的接口。 该接口可以例如被配置为以视觉方式呈现历史交易数据，其中定价数据例如交易价格，清单价格，预期销售价格或销售价格范围，市场低售价，市场平均值 销售价格，市场销售价格等相对于历史交易数据呈现。

公开(公告)号：US20130226945A1

公开(公告)日：2013-08-29

申请号：US13406325

申请日：2012-02-27

Applicant: Michael Swinson ,  Mikhail Semeniuk ,  Xingchu Liu

Inventor： Michael Swinson ,  Mikhail Semeniuk ,  Xingchu Liu

IPC: G06F17/30

CPC classification number: G06F17/30985 ,  G06F17/2795 ,  G06F17/30684 ,  G06Q30/0283

Abstract: Natural language processing (NLP) approaches may be utilized to map two strings. The strings may come from sources utilizing different naming conventions. One example may be a data aggregator that collects used car transaction information. Another example may be a comprehensive database listing all possible manufacturer-defined vehicle options. A NLP system may operate to determine whether a source string is present in a target string and outputting a match containing the source string and the target string if the source string is present in the target string or computing a similarity factor if the source string is not present in the target string. The similarity factor representing a measure of similarity between two strings may be computed based on a plurality of parameters, including a Levenshtein edit distance parameter. The computed similarity can be used to find pricing information, including trade-in, sale, and list prices, across disparate naming conventions.

Abstract translation: 自然语言处理（NLP）方法可用于映射两个字符串。 字符串可能来自使用不同命名约定的来源。 一个示例可以是收集二手车交易信息的数据聚合器。 另一个例子可能是列出所有可能的制造商定义的车辆选项的综合数据库。 如果源字符串存在于目标字符串中，则NLP系统可以操作以确定源字符串是否存在于目标字符串中并输出包含源字符串和目标字符串的匹配，或者如果源字符串不是，则输出相似因子 存在于目标字符串中。 可以基于包括Levenshtein编辑距离参数的多个参数来计算表示两个串之间的相似度的度量的相似性因子。 计算的相似性可以用于查找不同命名约定的定价信息，包括交易，销售和列表价格。

公开(公告)号：US20110082804A1

公开(公告)日：2011-04-07

申请号：US12896107

申请日：2010-10-01

Applicant: Michael Swinson ,  Jesse Toprak ,  Mikhail Semeniuk ,  Scott Painter

Inventor： Michael Swinson ,  Jesse Toprak ,  Mikhail Semeniuk ,  Scott Painter

IPC: G06Q99/00

CPC classification number: G06Q30/0206 ,  G06Q30/02 ,  G06Q30/0278

Abstract: Embodiments disclosed herein can provide consumers with an effective tool for evaluating the negotiability of prices for vehicles in the marketplace. The tool may include a Price Flexibility Score which measures the elasticity of transaction prices by vehicle model. Specifically, a method may dynamically incorporate factors that affect price variance, convert those factors into variables, generate order statistics for each of the variables, apply a weighting factor to the variables to generate a price flexibility score for each make-model, and determine a negotiability index utilizing the price flexibility score. In one embodiment, the process of determining the negotiability index may be fully driven by a price flexibility model that incorporates a plurality of factors.

Abstract translation: 本文公开的实施例可以向消费者提供用于评估市场中的车辆的价格的可协商性的有效工具。 该工具可以包括价格灵活性评分，其通过车辆模型测量交易价格的弹性。 具体来说，一种方法可以动态地并入影响价格差异的因素，将这些因素转换为变量，为每个变量生成订单统计量，将加权因子应用于变量以产生每个制造模型的价格弹性分数，并且确定 谈判价格指数利用价格弹性得分。 在一个实施例中，确定可转让性指数的过程可以由包含多个因素的价格弹性模型完全驱动。

公开(公告)号：US08781846B2

公开(公告)日：2014-07-15

申请号：US12896107

申请日：2010-10-01

Applicant: Michael Swinson ,  Jesse Toprak ,  Mikhail Semeniuk ,  Scott Painter

Inventor： Michael Swinson ,  Jesse Toprak ,  Mikhail Semeniuk ,  Scott Painter

IPC: G06Q10/00

CPC classification number: G06Q30/0206 ,  G06Q30/02 ,  G06Q30/0278

Abstract: Embodiments disclosed herein can provide consumers with an effective tool for evaluating the negotiability of prices for vehicles in the marketplace. The tool may include a Price Flexibility Score which measures the elasticity of transaction prices by vehicle model. Specifically, a method may dynamically incorporate factors that affect price variance, convert those factors into variables, generate order statistics for each of the variables, apply a weighting factor to the variables to generate a price flexibility score for each make-model, and determine a negotiability index utilizing the price flexibility score. In one embodiment, the process of determining the negotiability index may be fully driven by a price flexibility model that incorporates a plurality of factors.

Abstract translation: 本文公开的实施例可以向消费者提供用于评估市场中的车辆的价格的可协商性的有效工具。 该工具可以包括价格灵活性评分，其通过车辆模型测量交易价格的弹性。 具体来说，一种方法可以动态地并入影响价格差异的因素，将这些因素转换为变量，为每个变量生成订单统计量，将加权因子应用于变量以产生每个制造模型的价格弹性分数，并且确定 谈判价格指数利用价格弹性得分。 在一个实施例中，确定可转让性指数的过程可以由包含多个因素的价格弹性模型完全驱动。

公开(公告)号：US10296929B2

公开(公告)日：2019-05-21

申请号：US13173357

申请日：2011-06-30

Applicant: Michael Swinson ,  Param Pash Kaur Dhillon ,  Thomas J. Sullivan ,  Xingchu Liu

Inventor： Michael Swinson ,  Param Pash Kaur Dhillon ,  Thomas J. Sullivan ,  Xingchu Liu

IPC: G06Q30/02

Abstract: Disclosed are embodiments for the aggregation and analysis of vehicle prices via a geo-specific model. Data may be collected at various geo-specific levels such as a ZIP-Code level to provide greater data resolution. Data sets taken into account may include demarcation point data sets and data sets based on vehicle transactions. A demarcation point data set may be based on consumer market factors that influence car-buying behavior. Vehicle transactions may be classified into data sets for other vehicles having similar characteristics to the vehicle. A geo-specific statistical pricing model may then be applied to the data sets based on similar characteristics to a particular vehicle to produce a price estimation for the vehicle.

公开(公告)号：US08762219B2

公开(公告)日：2014-06-24

申请号：US13232444

申请日：2011-09-14

Applicant: Michael Swinson ,  Param Pash Kaur Dhillon ,  Xingchu Liu

Inventor： Michael Swinson ,  Param Pash Kaur Dhillon ,  Xingchu Liu

IPC: G06Q30/00 ,  G06Q30/02 ,  G06Q30/06

CPC classification number: G06Q30/02 ,  G06Q30/0613

Abstract: In response to a user request for information on the best/worst days in an upcoming time period to buy a commodity, a vehicle data system may determine anticipated daily discounts applicable to the commodity. An example commodity may be a vehicle of a specific configuration. In one embodiment, characteristics of month, day of week, and day of month may be gathered and fed into a Best Day to Buy model to determine, for each day of the time period, a projected daily discount relative to a set price for the commodity. Additional input variables such as incentives and seasonal discounts may be included. From the computed daily discounts, the vehicle data system may determine the best day and/or the worst day to buy and report same to the user.

Abstract translation: 响应于用户要求在即将到来的时间段内购买商品的最佳/最差天数的信息，车辆数据系统可以确定适用于商品的预期每日折扣。 示例商品可以是具体配置的载体。 在一个实施例中，可以收集月份，星期几和月份的特征，并且将其馈送到“最佳购买日”模型中，以确定每个时间段的每一天相对于 商品。 可能包括其他输入变量，如激励和季节性折扣。 从计算出的每日折扣中，车辆数据系统可以确定最佳的一天和/或最差的一天，以向用户购买和报告相同的日期。

公开(公告)号：US20130006876A1

公开(公告)日：2013-01-03

申请号：US13173357

申请日：2011-06-30

Applicant: Michael Swinson ,  Param Pash Kaur Dhillon ,  Thomas J. Sullivan ,  Xingchu Liu

Inventor： Michael Swinson ,  Param Pash Kaur Dhillon ,  Thomas J. Sullivan ,  Xingchu Liu

IPC: G06Q99/00

CPC classification number: G06Q30/0206 ,  G06Q30/02 ,  G06Q30/0205

Abstract: Disclosed are embodiments for the aggregation and analysis of vehicle prices via a geo-specific model. Data may be collected at various geo-specific levels such as a ZIP-Code level to provide greater data resolution. Data sets taken into account may include demarcation point data sets and data sets based on vehicle transactions. A demarcation point data set may be based on consumer market factors that influence car-buying behavior. Vehicle transactions may be classified into data sets for other vehicles having similar characteristics to the vehicle. A geo-specific statistical pricing model may then be applied to the data sets based on similar characteristics to a particular vehicle to produce a price estimation for the vehicle.

Abstract translation: 公开了通过地理特定模型来聚合和分析车辆价格的实施例。 可以在各种地理特定级别（例如ZIP-Code级别）收集数据以提供更大的数据分辨率。 考虑的数据集可以包括基于车辆交易的分界点数据集和数据集。 分界点数据集可以基于影响购车行为的消费者市场因素。 车辆交易​​可以分类为具有与车辆相似特征的其他车辆的数据集。 然后可以基于与特定车辆的相似特征将数据集合应用到地理特定的统计定价模型以产生车辆的价格估计。

公开(公告)号：US20120066092A1

公开(公告)日：2012-03-15

申请号：US13232444

申请日：2011-09-14

Applicant: Michael Swinson ,  Param Pash Kaur Dhillon ,  Xingchu Liu

Inventor： Michael Swinson ,  Param Pash Kaur Dhillon ,  Xingchu Liu

IPC: G06Q30/00

CPC classification number: G06Q30/02 ,  G06Q30/0613

Abstract: In response to a user request for information on the best/worst days in an upcoming time period to buy a commodity, a vehicle data system may determine anticipated daily discounts applicable to the commodity. An example commodity may be a vehicle of a specific configuration. In one embodiment, characteristics of month, day of week, and day of month may be gathered and fed into a Best Day to Buy model to determine, for each day of the time period, a projected daily discount relative to a set price for the commodity. Additional input variables such as incentives and seasonal discounts may be included. From the computed daily discounts, the vehicle data system may determine the best day and/or the worst day to buy and report same to the user.

Abstract translation: 响应于用户要求在即将到来的时间段内购买商品的最佳/最差天数的信息，车辆数据系统可以确定适用于商品的预期每日折扣。 示例商品可以是具体配置的载体。 在一个实施例中，可以收集月份，星期几和月份的特征，并且将其馈送到“最佳购买日”模型中，以确定每个时间段的每一天相对于 商品。 可能包括其他输入变量，如激励和季节性折扣。 从计算出的每日折扣中，车辆数据系统可以确定最佳的一天和/或最差的一天，以向用户购买和报告相同的日期。