Learning transportation modes from raw GPS data
    1.
    发明授权
    Learning transportation modes from raw GPS data 有权
    从原始GPS数据学习交通模式

    公开(公告)号:US08015144B2

    公开(公告)日:2011-09-06

    申请号:US12037305

    申请日:2008-02-26

    IPC分类号: G06F9/44 G06N7/02 G06N7/06

    摘要: Described is a technology by which raw GPS data is processed into segments of a trip, with a predicted mode of transportation (e.g., walking, car, bus, bicycling) determined for each segment. The determined transportation modes may be used to tag the GPS data with transportation mode information, and/or dynamically used. Segments are first characterized as walk segments or non-walk segments based on velocity and/or acceleration. Features corresponding to each of those walk segments or non-walk segments are extracted, and analyzed with an inference model to determine probabilities for the possible modes of transportation for each segment. Post-processing may be used to modify the probabilities based on transitioning considerations with respect to the transportation mode of an adjacent segment. The most probable transportation mode for each segment is selected.

    摘要翻译: 描述了一种将原始GPS数据处理成行程段的技术,其中为每个段确定了预测的运输方式(例如步行,汽车,公交车,骑自行车)。 确定的运输模式可以用于使用运输模式信息来标记GPS数据,和/或动态地使用。 首先基于速度和/或加速度将细分特征描述为步行段或非步行段。 提取对应于每个步行段或非步行段的特征,并用推理模型分析以确定每个段的可能运输模式的概率。 可以使用后处理来基于相对于相邻段的传送模式的转换考虑来修改概率。 选择每个段最可能的运输模式。

    Learning transportation modes from raw GPS data
    2.
    发明授权
    Learning transportation modes from raw GPS data 有权
    从原始GPS数据学习交通模式

    公开(公告)号:US08315959B2

    公开(公告)日:2012-11-20

    申请号:US13195496

    申请日:2011-08-01

    IPC分类号: G06F15/18

    摘要: Described is a technology by which raw GPS data is processed into segments of a trip, with a predicted mode of transportation (e.g., walking, car, bus, bicycling) determined for each segment. The determined transportation modes may be used to tag the GPS data with transportation mode information, and/or dynamically used. Segments are first characterized as walk segments or non-walk segments based on velocity and/or acceleration. Features corresponding to each of those walk segments or non-walk segments are extracted, and analyzed with an inference model to determine probabilities for the possible modes of transportation for each segment. Post-processing may be used to modify the probabilities based on transitioning considerations with respect to the transportation mode of an adjacent segment. The most probable transportation mode for each segment is selected.

    摘要翻译: 描述了一种将原始GPS数据处理成行程段的技术,其中为每个段确定了预测的运输方式(例如步行,汽车,公交车,骑自行车)。 确定的运输模式可以用于使用运输模式信息来标记GPS数据,和/或动态地使用。 首先基于速度和/或加速度将细分特征描述为步行段或非步行段。 提取对应于每个步行段或非步行段的特征,并用推理模型分析以确定每个段的可能运输模式的概率。 可以使用后处理来基于相对于相邻段的传送模式的转换考虑来修改概率。 选择每个段最可能的运输模式。

    LEARNING TRANSPORTATION MODES FROM RAW GPS DATA
    3.
    发明申请
    LEARNING TRANSPORTATION MODES FROM RAW GPS DATA 有权
    从原始GPS数据学习运输模式

    公开(公告)号:US20110289031A1

    公开(公告)日:2011-11-24

    申请号:US13195496

    申请日:2011-08-01

    IPC分类号: G06F15/18 G06N5/04

    摘要: Described is a technology by which raw GPS data is processed into segments of a trip, with a predicted mode of transportation (e.g., walking, car, bus, bicycling) determined for each segment. The determined transportation modes may be used to tag the GPS data with transportation mode information, and/or dynamically used. Segments are first characterized as walk segments or non-walk segments based on velocity and/or acceleration. Features corresponding to each of those walk segments or non-walk segments are extracted, and analyzed with an inference model to determine probabilities for the possible modes of transportation for each segment. Post-processing may be used to modify the probabilities based on transitioning considerations with respect to the transportation mode of an adjacent segment. The most probable transportation mode for each segment is selected.

    摘要翻译: 描述了一种将原始GPS数据处理成行程段的技术,其中为每个段确定了预测的运输方式(例如步行,汽车,公交车,骑自行车)。 确定的运输模式可以用于使用运输模式信息来标记GPS数据,和/或动态地使用。 首先基于速度和/或加速度将细分特征描述为步行段或非步行段。 提取对应于每个步行段或非步行段的特征,并用推理模型分析以确定每个段的可能运输模式的概率。 可以使用后处理来基于相对于相邻段的传送模式的转换考虑来修改概率。 选择每个段最可能的运输模式。

    LEARNING TRANSPORTATION MODES FROM RAW GPS DATA
    4.
    发明申请
    LEARNING TRANSPORTATION MODES FROM RAW GPS DATA 有权
    从原始GPS数据学习运输模式

    公开(公告)号:US20090216704A1

    公开(公告)日:2009-08-27

    申请号:US12037305

    申请日:2008-02-26

    IPC分类号: G06N7/02 G06F17/30 G06N5/02

    摘要: Described is a technology by which raw GPS data is processed into segments of a trip, with a predicted mode of transportation (e.g., walking, car, bus, bicycling) determined for each segment. The determined transportation modes may be used to tag the GPS data with transportation mode information, and/or dynamically used. Segments are first characterized as walk segments or non-walk segments based on velocity and/or acceleration. Features corresponding to each of those walk segments or non-walk segments are extracted, and analyzed with an inference model to determine probabilities for the possible modes of transportation for each segment. Post-processing may be used to modify the probabilities based on transitioning considerations with respect to the transportation mode of an adjacent segment. The most probable transportation mode for each segment is selected.

    摘要翻译: 描述了一种将原始GPS数据处理成行程段的技术,其中为每个段确定了预测的运输方式(例如步行,汽车,公交车,骑自行车)。 确定的运输模式可以用于使用运输模式信息来标记GPS数据,和/或动态地使用。 首先基于速度和/或加速度将细分特征描述为步行段或非步行段。 提取对应于每个步行段或非步行段的特征,并用推理模型分析以确定每个段的可能运输模式的概率。 可以使用后处理来基于相对于相邻段的传送模式的转换考虑来修改概率。 选择每个段最可能的运输模式。

    Indexing large-scale GPS tracks
    5.
    发明授权
    Indexing large-scale GPS tracks 有权
    索引大型GPS轨道

    公开(公告)号:US08078394B2

    公开(公告)日:2011-12-13

    申请号:US12037263

    申请日:2008-02-26

    IPC分类号: G06F17/00

    摘要: Described is a technology by which uploaded GPS data is indexed according to spatio-temporal relationships to facilitate efficient insertion and retrieval. The indexes may be converted to significantly smaller-sized data structures when new updates to that structure are not likely. GPS data is processed into a track of spatially-partitioned segments such that each segment has a cell. Each cell has an associated temporal index (a compressed start-end tree), into which data for that cell's segments are inserted. The temporal index may include an end time index that relates each segment's end time to a matching start time index. Given query input comprising a spatial predicate and a temporal predicate, tracks may be searched for by determining which spatial candidate cells may contain matching results. For each candidate cell, the search accesses the cell's associated temporal index to find any track or tracks that correspond to the temporal predicate.

    摘要翻译: 描述了一种根据时空关系对上传的GPS数据进行索引的技术,以便于有效的插入和检索。 当该结构的新更新不太可能时,索引可能会转换为显着更小的数据结构。 GPS数据被处理成空间分割的段的轨道,使得每个段具有一个单元。 每个单元都具有关联的时间索引(压缩的开始结束树),该单元格的段的数据被插入到该时间索引中。 时间索引可以包括将每个段的结束时间与匹配的开始时间索引相关联的结束时间索引。 给定包括空间谓词和时间谓词的查询输入,可以通过确定哪些空间候选小区可以包含匹配结果来搜索轨道。 对于每个候选小区,搜索访问小区的相关联的时间索引以找到与时间谓词相对应的任何轨道或​​轨道。

    INDEXING LARGE-SCALE GPS TRACKS
    6.
    发明申请
    INDEXING LARGE-SCALE GPS TRACKS 有权
    引导大规模GPS跟踪

    公开(公告)号:US20090216787A1

    公开(公告)日:2009-08-27

    申请号:US12037263

    申请日:2008-02-26

    IPC分类号: G06F7/00 G06F17/30

    摘要: Described is a technology by which uploaded GPS data is indexed according to spatio-temporal relationships to facilitate efficient insertion and retrieval. The indexes may be converted to significantly smaller-sized data structures when new updates to that structure are not likely. GPS data is processed into a track of spatially-partitioned segments such that each segment has a cell. Each cell has an associated temporal index (a compressed start-end tree), into which data for that cell's segments are inserted. The temporal index may include an end time index that relates each segment's end time to a matching start time index. Given query input comprising a spatial predicate and a temporal predicate, tracks may be searched for by determining which spatial candidate cells may contain matching results. For each candidate cell, the search accesses the cell's associated temporal index to find any track or tracks that correspond to the temporal predicate.

    摘要翻译: 描述了一种根据时空关系对上传的GPS数据进行索引的技术,以便于有效的插入和检索。 当该结构的新更新不太可能时,索引可能会转换为显着更小的数据结构。 GPS数据被处理成空间分割的段的轨道,使得每个段具有一个单元。 每个单元都具有关联的时间索引(压缩的开始结束树),该单元格的段的数据被插入到该时间索引中。 时间索引可以包括将每个段的结束时间与匹配的开始时间索引相关联的结束时间索引。 给定包括空间谓词和时间谓词的查询输入,可以通过确定哪些空间候选小区可以包含匹配结果来搜索轨道。 对于每个候选小区,搜索访问小区的相关联的时间索引以找到与时间谓词相对应的任何轨道或​​轨道。

    System for logging life experiences using geographic cues
    7.
    发明授权
    System for logging life experiences using geographic cues 有权
    使用地理线索记录生活体验的系统

    公开(公告)号:US08972177B2

    公开(公告)日:2015-03-03

    申请号:US12037347

    申请日:2008-02-26

    摘要: A system logs life experiences using geographic cues. The system variously provides a comprehensive life-logging tool for recording a plurality of different types of life events. In one implementation, the system receives a user's GPS log files and multimedia content at a website. The system segments the GPS log files into geographic routes corresponding to user trips, and tags the multimedia content with geographic cues from the GPS log files. Then, the system indexes the geographic routes so that users can retrieve the geographic routes by browsing or by search techniques. The system displays animations of selected routes on a map, and displays the multimedia content at corresponding locations along the map route, as the route is replayed. The system also provides browsing and spatial and temporal techniques to search a person's travels and can provide graphical displays of the person's activity statistics.

    摘要翻译: 系统使用地理线索记录生活体验。 该系统各种地提供了用于记录多种不同类型的生命事件的全面的生命测井工具。 在一个实现中,系统在网站上接收用户的GPS日志文件和多媒体内容。 系统将GPS日志文件分割成与用户跳闸对应的地理路线,并使用GPS日志文件中的地理线索标记多媒体内容。 然后,系统对地理路径进行索引,以便用户可以通过浏览或搜索技术来检索地理路由。 该系统在地图上显示所选择的路线的动画,并且在重放路线时,沿着地图路线的相应位置显示多媒体内容。 该系统还提供浏览和空间和时间技术来搜索个人的旅行,并且可以提供该人的活动统计的图形显示。

    SYSTEM FOR LOGGING LIFE EXPERIENCES USING GEOGRAPHIC CUES
    8.
    发明申请
    SYSTEM FOR LOGGING LIFE EXPERIENCES USING GEOGRAPHIC CUES 有权
    使用地理位置登录生活体验的制度

    公开(公告)号:US20090216435A1

    公开(公告)日:2009-08-27

    申请号:US12037347

    申请日:2008-02-26

    IPC分类号: G01C21/34 G06F7/06 G06F17/30

    摘要: A system for logging life experiences using geographic cues. The system variously provides a comprehensive life-logging tool for recording each life event; a vacation album for revisiting and reliving vacation routes and associated photos; an information service for finding popular routes and locations; a statistical tool for analyzing metrics of a person's life; and a personal website service for sharing personal information. In one implementation, the system receives a user's GPS log files and multimedia content at a website. The system segments the GPS log files into geographic routes corresponding to user trips, and tags the multimedia content with geographic cues from the GPS log files. Then, the system indexes the geographic routes so that users can retrieve the geographic routes by browsing or by search techniques. The system displays animations of selected routes on a map, and displays the multimedia content at corresponding locations along the map route, as the route is replayed. The system also provides browsing and spatial and temporal techniques to search a person's travels and can provide graphical displays of the person's activity statistics.

    摘要翻译: 使用地理线索记录生活经验的系统。 该系统为记录每个人生活动提供了全面的生命记录工具; 一个度假专辑,用于重温和重温假期路线和相关照片; 寻找流行路线和位置的信息服务; 用于分析人的生活指标的统计工具; 以及个人网站服务,用于分享个人信息。 在一个实现中,系统在网站上接收用户的GPS日志文件和多媒体内容。 系统将GPS日志文件分割成与用户跳闸对应的地理路线,并使用GPS日志文件中的地理线索标记多媒体内容。 然后,系统对地理路径进行索引,以便用户可以通过浏览或搜索技术来检索地理路由。 该系统在地图上显示所选择的路线的动画,并且在重放路线时,沿着地图路线的相应位置显示多媒体内容。 该系统还提供浏览和空间和时间技术来搜索个人的旅行,并且可以提供该人的活动统计的图形显示。

    Discovering co-located queries in geographic search logs
    9.
    发明授权
    Discovering co-located queries in geographic search logs 有权
    在地理搜索日志中发现同位置查询

    公开(公告)号:US09092454B2

    公开(公告)日:2015-07-28

    申请号:US12147868

    申请日:2008-06-27

    IPC分类号: G06F7/00 G06F17/30

    CPC分类号: G06F17/30241 G06F17/30041

    摘要: Described is a technology by which co-located query patterns are mined from a data space such as a geographic search log. An overall data space (basic) approach and/or a lattice-based approach may be used when mining. The data space contains objects, each comprising associated type and location information. The location information is used to determine the distance between different two or more types of objects, e.g., pairs. The frequency of occurrence of those pairs within the data space determines whether that pairing of object types indicates a co-located pattern. Also described is partitioning the data space into regions, including for the purpose of categorizing a co-located pattern as a local pattern or a global pattern based on how that co-located pattern is distributed among the regions.

    摘要翻译: 描述了从地理搜索日志等数据空间挖掘共同查询模式的技术。 在开采时可以使用总体数据空间(基本)方法和/或基于格子的方法。 数据空间包含对象,每个对象包括关联的类型和位置信息。 位置信息用于确定不同的两种或多种类型的对象(例如,对)之间的距离。 数据空间内这些对的出现频率决定对象类型的配对是否表示共同定位的模式。 还描述了将数据空间划分为区域,包括为了基于如何在区域之间分配共同定位模式将共定位模式分类为局部模式或全局模式。

    DISCOVERING CO-LOCATED QUERIES IN GEOGRAPHIC SEARCH LOGS
    10.
    发明申请
    DISCOVERING CO-LOCATED QUERIES IN GEOGRAPHIC SEARCH LOGS 有权
    在地理搜索日志中发现协同查询

    公开(公告)号:US20090265388A1

    公开(公告)日:2009-10-22

    申请号:US12147868

    申请日:2008-06-27

    IPC分类号: G06F17/30

    CPC分类号: G06F17/30241 G06F17/30041

    摘要: Described is a technology by which co-located query patterns are mined from a data space such as a geographic search log. An overall data space (basic) approach and/or a lattice-based approach may be used when mining. The data space contains objects, each comprising associated type and location information. The location information is used to determine the distance between different two or more types of objects, e.g., pairs. The frequency of occurrence of those pairs within the data space determines whether that pairing of object types indicates a co-located pattern. Also described is partitioning the data space into regions, including for the purpose of categorizing a co-located pattern as a local pattern or a global pattern based on how that co-located pattern is distributed among the regions.

    摘要翻译: 描述了从地理搜索日志等数据空间挖掘共同查询模式的技术。 在开采时可以使用总体数据空间(基本)方法和/或基于格子的方法。 数据空间包含对象,每个对象包括关联的类型和位置信息。 位置信息用于确定不同的两种或多种类型的对象(例如,对)之间的距离。 数据空间内这些对的出现频率决定对象类型的配对是否表示共同定位的模式。 还描述了将数据空间划分为区域,包括为了基于如何在区域之间分配共同定位模式将共定位模式分类为局部模式或全局模式。