Patent application number | Description | Published |
20090216435 | SYSTEM FOR LOGGING LIFE EXPERIENCES USING GEOGRAPHIC CUES - 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. | 08-27-2009 |
20090216704 | LEARNING TRANSPORTATION MODES FROM RAW GPS DATA - 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. | 08-27-2009 |
20090216787 | INDEXING LARGE-SCALE GPS TRACKS - 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. | 08-27-2009 |
20100153292 | Making Friend and Location Recommendations Based on Location Similarities - Method for making a recommendation to a first user in a computing network, including calculating one or more similarity scores between the first user and one or more remaining users in the network, identifying a portion of the remaining users having a highest similarity scores, identifying one or more locations visited by the portion of the remaining users but not by the first user, determining an interest level of the first user in each location, ranking the locations based on the interest levels, and displaying the locations based on the ranking as a first recommendation. | 06-17-2010 |
20100179759 | Detecting Spatial Outliers in a Location Entity Dataset - Disclosed herein are one or more embodiments that arrange a plurality of location entities into a hierarchy of location descriptors. One or more of the disclosed embodiments may determine whether one of the location entities is a spatial outlier based at least in part on presence of one or more other location entities within a predetermined distance of the one location entity. Also, the other location entities and the one location entity may share a location descriptor. | 07-15-2010 |
20100211308 | IDENTIFYING INTERESTING LOCATIONS - Interesting location identification embodiments are presented that generally involve identifying and providing the interesting locations found in a given geospatial region. This is accomplished by modeling the location histories of multiple individuals who traveled through the region of interest, and identifying interesting locations in the region based on the number of individuals visiting a location weighted in terms of the travel experience of those individuals. A prescribed number of the top most interesting locations in a specified region can be provided upon request. In addition, prescribed numbers of the top most popular travel sequences through the interesting locations and the top most experienced travelers in the specified region can be provided as well. | 08-19-2010 |
20100306233 | SEARCH AND REPLAY OF EXPERIENCES BASED ON GEOGRAPHIC LOCATIONS - Users are enabled to record and retrieve their experiences temporally and based on geographic locations. Experiences such as meetings, conferences, emails, other forms of communications are indexed along a timeline and associated with geographic locations. A user interface provides replay of experiences with links to associated documents, recordings, etc. employing a user friendly map feature. | 12-02-2010 |
20100311395 | NEARBY CONTACT ALERT BASED ON LOCATION AND CONTEXT - Attributes including presence and organization information for contacts of a subscriber are used in determining a subset of contacts matching a predefined criterion. Determined subset of contacts is sent as an alert to notify the subscriber to the subsets' nearby proximity. | 12-09-2010 |
20100316205 | CALL ROUTING AND PRIORITIZATION BASED ON LOCATION CONTEXT - Called parties in an enhanced communication system are provided location information associated with a calling party to help them determine whether they should accept the call. Alternatively, automatic call routing may be performed based on location context information associated with the calling party such as whether the caller is calling from a regular location association with him/her or an extra-ordinary location. | 12-16-2010 |
20110071881 | MINING LIFE PATTERN BASED ON LOCATION HISTORY - Techniques for providing mining life pattern are described. This disclosure describes mining a life pattern of an individual, for example, by identifying places visited during the individual's daily activities. Mining the individual life pattern includes collecting location data for the individual and predicting behaviors and preferences of the individual based at least in part on a location history. The location history of the individual is represented with a sequence of geographical regions that have been visited by the individual with corresponding arrival and departure times for each region. Once the life pattern is predicted from the location history, information is recommended to the individual based at least in part on the life pattern. | 03-24-2011 |
20110093458 | RECOMMENDING POINTS OF INTERESTS IN A REGION - Techniques for searching and providing geographical regions are described. The process searches and recommends points of interests based on a user-specified region. Points of interests include spatial objects (e.g., buildings, landmarks, rivers, parks) and their distributions in a geographical region. The process searches and recommends points of interests by partitioning a spatial map into grids to identify representative categories located in each of the grids. In response to the user-specified region, a set of geographical candidates containing the representative categories is retrieved. The process determines whether the user-specified region and the set of geographical candidates include similar or common representative categories and similar or common spatial distributions of the representative categories. Then the process provides the top ranked set of geographical candidates that have similar content information. | 04-21-2011 |
20110208425 | Mining Correlation Between Locations Using Location History - Techniques describe determining a correlation between identified locations to recommend a location that may be of interest to an individual user. The process constructs a location model to identify locations. To construct the model, the process uses global positioning system (GPS) logs of geospatial locations collected over time and identifies trajectories representing trips of the individual user and extracts stay points from the trajectories. Each stay point represents a geographical region where the individual user stayed over a time threshold within a distance threshold. A location history is formulated for the individual user based on a sequence of the extracted stay points to identify locations. | 08-25-2011 |
20110208426 | Map-Matching for Low-Sampling-Rate GPS Trajectories - This disclosure describes a map-matching module that supports a Global Positioning System (GPS) and provides a user with a best match trajectory corresponding to GPS sampling points taken at a low sampling rate. The best match trajectory is based upon a spatial-temporal analysis. | 08-25-2011 |
20110208429 | Route Computation Based on Route-Oriented Vehicle Trajectories - Techniques for providing a route based on route-oriented vehicle trajectories are described. This disclosure describes receiving GPS logs and extracting route-oriented vehicle trajectory content from the GPS log data to pertain to a single trip. Next, the process maps each route-oriented vehicle trajectory to a corresponding road segment to construct a landmark graph. A landmark is a road segment frequently visited by route-oriented vehicles. The process includes receiving a user query with a starting point and a destination point; searching the landmark graph for a sequence of landmarks with corresponding transition times and a least amount of travel time. Then the process identifies and connects sets of road segments between each pair of consecutive landmarks, and displays a route to a user with a nearest landmark to the starting point, other landmarks along the route, and another nearest landmark to the destination point. | 08-25-2011 |
20110276565 | Collaborative Location and Activity Recommendations - Techniques describe constructing a location and activity recommendation model to identify relationships between locations and activities. To construct the model, the process obtains global positioning system (GPS) logs of geographical locations collected over time and identifies stay points representing locations visited by an individual user. The process also identifies points of interest in a region using a database and correlates a relationship between activity to activity by submitting queries to a search engine. The information gathered is used to fill locations and activities in a location-activity matrix. Recommendations may be made for a location and/or activity when given a user query, based on a user's present geographical location, or a prediction of a user's interest. | 11-10-2011 |
20110282798 | Making Friend and Location Recommendations Based on Location Similarities - Method for making a recommendation to a first user in a computing network, including calculating one or more similarity scores between the first user and one or more remaining users in the network, identifying a portion of the remaining users having a highest similarity scores, identifying one or more locations visited by the portion of the remaining users but not by the first user, determining an interest level of the first user in each location, ranking the locations based on the interest levels, and displaying the locations based on the ranking as a first recommendation. | 11-17-2011 |
20110289031 | LEARNING TRANSPORTATION MODES FROM RAW GPS DATA - 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. | 11-24-2011 |
20110301832 | Searching Similar Trajectories by Locations - Techniques for providing a trajectory route to multiple geographical locations of interest are described. This disclosure describes receiving global position system (GPS) logs associated with respective individual devices, each of the GPS logs including trajectories connecting a set of geographical locations previously visited by an individual of a respective individual device. A trajectory route service receives a request for a trajectory connecting a set of geographical locations of interest specified by a user. The trajectory route service calculates a proximal similarity between (1) the set of geographical locations of interest specified by the user, and (2) respective sets of geographical locations from the GPS logs. The trajectory route service constructs the requested trajectory with use of at least one of the trajectories from the GPS logs determined at least in part according to the calculated proximal similarities. | 12-08-2011 |
20120047175 | Short Point-Of-Interest Title Generation - Short POI titles are generated by removing unnecessary administrative area prefixes from existing POI titles and replacing necessary administrative area prefixes with shorter aliases. Administrative area prefixes are identified and analyzed to determine whether they are necessary. The analysis includes determining (1) whether the remainders with the prefixes excluded include a common suffix as a prefix, and (2) whether the remainders are unique in an applicable metropolis area. If a remainder does not include as a prefix a common suffix and is unique in the applicable metropolis area, the corresponding prefix is determined unnecessary and removed from the existing POI title to generate a short POI title. Otherwise, the corresponding prefix is determined necessary and replaced with a shorter alias to generate a short POI title. | 02-23-2012 |
20120143882 | PRIORITIZING TRAVEL ITINERARIES - One or more techniques and/or systems are disclosed for prioritizing one or more travel itineraries based on an itinerary query. Respective candidate itineraries from a set of candidate itineraries are ranked based on one or more ranking factors for the candidate itineraries, where the candidate itineraries were identified from a location-interest graph using the query. A desired number of the ranked candidate itineraries are re-ranked based on a one or more historical travel sequences, such that one or more prioritized travel itineraries can be identified in response to the itinerary query. | 06-07-2012 |
20120278360 | Short Point-of-Interest Title Generation - Short POI titles are generated by removing unnecessary administrative area prefixes from existing POI titles and replacing necessary administrative area prefixes with shorter aliases. Administrative area prefixes are identified and analyzed to determine whether they are necessary. The analysis includes determining (1) whether the remainders with the prefixes excluded include a common suffix as a prefix, and (2) whether the remainders are unique in an applicable metropolis area. If a remainder does not include as a prefix a common suffix and is unique in the applicable metropolis area, the corresponding prefix is determined unnecessary and removed from the existing POI title to generate a short POI title. Otherwise, the corresponding prefix is determined necessary and replaced with a shorter alias to generate a short POI title. | 11-01-2012 |
20120296560 | Inferring a Behavioral State of a Vehicle - Trajectory data representing tracked positions of a vehicle along a trajectory having a start and end point is accessed. The trajectory data may include spatio-temporal information about the vehicle at different points along the trajectory. The trajectory may be divided into segments based, at least in part, on knowledge of inferred-parking locations. The segments may be map-matched to corresponding road segments. Additionally, historical data representing spatio-temporal travel patterns of vehicles learned from historical trajectories of vehicles corresponding to the map-matched-road segments may also be accessed. A behavioral state of the vehicle for a segment or position within a segment may be inferred, based at least in part, on (i) the vehicle's spatio-temporal information corresponding to the segment or position within a segment, (ii) knowledge of the map-matched-road segment, and (iii) the historical data. | 11-22-2012 |
20130073202 | LEARNING TRANSPORTATION MODES FROM RAW GPS DATA - 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. | 03-21-2013 |
20130151297 | Urban Computing of Route-Oriented Vehicles - Techniques for analyzing effectiveness of an urban area based on traffic patterns collected from route-oriented vehicles. A process collects sequences of global positioning system (GPS) points in logs and identifies geographical locations to represent the urban area where the route-oriented vehicles traveled. The process models traffic patterns by: partitioning the urban area into regions based at least in part on major roads, segmenting the GPS points from the logs into time slots, and identifying the GPS points associated with transporting a passenger in the route-oriented vehicles. The process models traffic patterns by projecting the identified GPS points onto the regions to construct transitions of the identified GPS points travelling between the regions. Then the process builds a matrix of the regions for each time slot in each day based on a number of the transitions. Each item in the matrix represents an effectiveness of a connection between two regions. | 06-13-2013 |
20130166188 | Determine Spatiotemporal Causal Interactions In Data - Techniques for detecting outliers in data and determining spatiotemporal causal interactions in the data are discussed. A process collects global positioning system (GPS) points in logs and identifies geographical locations to represent the area where the service vehicles travelled with a passenger. The process models traffic patterns by: partitioning the area into regions, segmenting the GPS points from the logs into time bins, and identifying the GPS points associated with transporting the passenger. The process projects the identified GPS points onto the regions to construct links connecting GPS points located in two or more regions. Furthermore, the process builds a three-dimensional unit cube to represent features of each link. The points farthest away from a center of data cluster are detected as outliers, which represent abnormal traffic patterns. The process constructs outlier trees to evaluate relationships of the outliers and determines the spatiotemporal causal interactions in the data. | 06-27-2013 |
20140278291 | DISCOVERING FUNCTIONAL GROUPS - Disclosed herein are techniques and systems for discovering functional groups in an area, such as an urban area. A process includes segmenting a map of the area into sections, and inferring, for each section, a distribution of functions according to a topic model framework which considers mobility patters of users and points of interest (POIs) in the section. The topic model framework regards the section as a document, each function as a topic, the mobility patterns as words, and a POI feature vector for the section as metadata. The process may further include clustering the sections based at least in part on a similarity of the distribution of functions between each of the sections to obtain functional groups, estimating a functionality intensity for each of the functional groups, and annotating each of the functional groups. | 09-18-2014 |