Patent application number | Description | Published |
20090285487 | Systems and methods for linking content to individual image features - A method, computer program, and system for linking content to individual image features are provided. A section of an image is identified. A plurality of features associated with the section of the image is determined. Each of the plurality of features corresponds to at least one position within the section of the image. Content associated with the plurality of features is retrieved from a content repository. The content is linked to the plurality of features based on at least one rule. The content is then presented. | 11-19-2009 |
20110007941 | PRECISELY LOCATING FEATURES ON GEOSPATIAL IMAGERY - Methods for locating a feature on geospatial imagery and systems for performing those methods are disclosed. An accuracy level of each of a plurality of geospatial vector datasets available in a database can be determined. Each of the plurality of geospatial vector datasets corresponds to the same spatial region as the geospatial imagery. The geospatial vector dataset having the highest accuracy level may be selected. When the selected geospatial vector dataset and the geospatial imagery are misaligned, the selected geospatial vector dataset is aligned to the geospatial imagery. The location of the feature on the geospatial imagery is then determined based on the selected geospatial vector dataset and outputted via a display device. | 01-13-2011 |
20110119265 | DYNAMICALLY LINKING RELEVANT DOCUMENTS TO REGIONS OF INTEREST - Document relevance is determined with respect to a region of interest (ROI). A set of location references may be associated with a set of documents. The system selects location references associated with an ROI and then selects documents corresponding to the selected location references. The selected documents can be reported or processed further. A document-location reference index can be accessed when the present system is ‘online’ and processing a request for documents relevant to an ROI. The document-location reference index may be generated and updated while the present system is ‘offline’ and not processing a request for documents. The resulting relevant documents may be provided to a user in response to a document search associated with the ROI or along with an advertisement associated with the ROI. | 05-19-2011 |
20110123066 | PRECISELY LOCATING FEATURES ON GEOSPATIAL IMAGERY - Methods for locating a feature on geospatial imagery and systems for performing those methods are disclosed. An accuracy level of each of a plurality of geospatial vector datasets available in a database can be determined. Each of the plurality of geospatial vector datasets corresponds to the same spatial region as the geospatial imagery. The geospatial vector dataset having the highest accuracy level may be selected. When the selected geospatial vector dataset and the geospatial imagery are misaligned, the selected geospatial vector dataset is aligned to the geospatial imagery. The location of the feature on the geospatial imagery is then determined based on the selected geospatial vector dataset and outputted via a display device. | 05-26-2011 |
20110142347 | PROCESSING TIME-BASED GEOSPATIAL DATA - A method for processing geospatial datasets corresponding to geospatial objects, the method having the steps of extracting geospatial attributes from the geospatial datasets, locating extracted geospatial attributes corresponding to a particular geospatial object at a particular point in time, and generating output indicative of the particular geospatial object at the particular point in time utilizing the located geospatial attributes. | 06-16-2011 |
20110280453 | System and Method for Fusing Geospatial Data - Automatic conflation systems and techniques which provide vector-imagery conflation and map-imagery conflation. Vector-imagery conflation is an efficient approach that exploits knowledge from multiple data sources to identify a set of accurate control points. Vector-imagery conflation provides automatic and accurate alignment of various vector datasets and imagery, and is appropriate for GIS applications, for example, requiring alignment of vector data and imagery over large geographical regions. Map-imagery conflation utilizes common vector datasets as “glue” to automatically integrate street maps with imagery. This approach provides automatic, accurate, and intelligent images that combine the visual appeal and accuracy of imagery with the detailed attribution information often contained in such diverse maps. Both conflation approaches are applicable for GIS applications requiring, for example, alignment of vector data, raster maps, and imagery. If desired, the conflated data generated by such systems may be retrieved on-demand. | 11-17-2011 |
20120278310 | Collaborative Filtering Using a Spatial-Aware Social Graph - This specification describes technologies relating to collaborative filtering, such as collaborative filtering using a spatial-aware social graph. In at least one aspect, a method includes: receiving data including objects related to a social graph; identifying a proper subset of the objects based on their relationships with respect to the social graph; applying one or more spatial queries against the proper subset of the objects; and using a result of the one or more spatial queries, applied against the proper subset of the objects, as a feature in a recommendation process. In another aspect, a system includes: a user interface device; and one or more computers configured and arranged to provide a user a recommendation, with respect to objects, based on social and spatial information for the user associated with a spatial-aware social graph. | 11-01-2012 |
20120283948 | Hierarchical and Exact Fastest Path Computation in Time-dependent Spatial Networks - With real-world spatial networks the edge travel-times are time-dependent, where the arrival-time to an edge determines the actual travel-time on the edge. To speed up the path computation, exact and approximate techniques for computation of the fastest path in time-dependent spatial networks are presented. An exact fastest path computation technique based on a time-dependent A* search can significantly improve the computation time and storage complexity of existing approaches. Moreover, for applications with which approximate fastest path is acceptable, the approximate fastest path computation technique can improve the computation time by an order of magnitude while maintaining high accuracy (e.g., with only 7% increase in travel-time of the computed path on average). With experiments using real data-sets (including a variety of large spatial networks with real traffic data) the efficacy of the disclosed techniques for online fastest path computation is demonstrated. | 11-08-2012 |
20140046593 | Efficient K-Nearest Neighbor Search in Time-Dependent Spatial Networks - The class of k Nearest Neighbor (k NN) queries in spatial networks has been studied in the literature. Existing approaches for k NN search in spatial networks assume that the weight of each edge in the spatial network is constant. However, real-world edge-weights are time-dependent and vary significantly in short durations, hence invalidating the existing solutions. The problem of k NN search in time-dependent spatial networks, where the weight of each edge is a function of time, is addressed herein. Two indexing schemes (Tight Network Index and Loose Network Index) are proposed to minimize the number of candidate nearest neighbor objects and reduce the invocation of the expensive fastest-path computation in time-dependent spatial networks. We demonstrate the efficiency of our proposed solution via experimental evaluations with real-world data-sets, including a variety of large spatial networks with real traffic-data. | 02-13-2014 |
20140114556 | TRAFFIC PREDICTION USING REAL-WORLD TRANSPORTATION DATA - Real-time high-fidelity spatiotemporal data on transportation networks can be used to learn about traffic behavior at different times and locations, potentially resulting in major savings in time and fuel. Real-world data collected from transportation networks can be used to incorporate the data's intrinsic behavior into a time-series mining technique to enhance its accuracy for traffic prediction. For example, the spatiotemporal behaviors of rush hours and events can be used to perform a more accurate prediction of both short-term and long-term average speed on road-segments, even in the presence of infrequent events (e.g., accidents). Taking historical rush-hour behavior into account can improve the accuracy of traditional predictors by up to 67% and 78% in short-term and long-term predictions, respectively. Moreover, the impact of an accident can be incorporated to improve the prediction accuracy by up to 91%. | 04-24-2014 |
20140343984 | SPATIAL CROWDSOURCING WITH TRUSTWORTHY QUERY ANSWERING - Spatial crowdsourcing systems and methods assign spatial tasks to be performed by human workers. The systems and methods can verify the validity of the results provided by workers. Every worker can have a reputation score stating the probability that the worker performs a task correctly. Every spatial task can have a confidence threshold determining the minimum quality of the accepted level of its result. To satisfy this threshold, a task may be assigned redundantly to multiple workers. A reputation score can be associated to every worker, which represents the probability that a worker performs a task correctly. A task may be assigned to a subset of workers whose aggregate reputation score satisfies the confidence of the task. | 11-20-2014 |