Abstract: A method for automatically generating, in real-time, for display on a display, a simplified network layout from an initial network layout including one or more lines each connecting a plurality of nodes. Graph information is provided indicating vertices representing geographic positions of the nodes and edges representing connections between the nodes. The nodes are repositioned to optimize an objective function based on readability of the simplified network layout. Nodes and edges are discretized using interpolation to align a plurality of the nodes and connect the aligned nodes using simplified k-linear segments, where k-linear segments are parallel to one of k equidistant orientations whose angles are multiples of 180/k degrees, with k larger or equal to two. The simplified network layout is provided for a display.

Abstract: A method for automatically generating, in real-time, for display on a display, a simplified network layout from an initial network layout including one or more lines each connecting a plurality of nodes. Graph information is provided indicating vertices representing geographic positions of the nodes and edges representing connections between the nodes. The nodes are repositioned to optimize an objective function based on readability of the simplified network layout. Nodes and edges are discretized using interpolation to align a plurality of the nodes and connect the aligned nodes using simplified k-linear segments, where k-linear segments are parallel to one of k equidistant orientations whose angles are multiples of 180/k degrees, with k larger or equal to two. The simplified network layout is provided for a display.

Abstract: A computer-implemented method for accurately and efficiently generating ambient point-of-interest recommendations electronically obtains a plurality of points-of-interest for an area, the area being an area selected by a user associated with a location of the user; electronically retrieves point-of-interest data including visitor information about visitors associated with the obtained plurality of points-of-interest and information about the obtained plurality of points-of-interest; electronically forms a plurality of groups based upon the visitor information, each group of the plurality of groups being associated with a point-of-interest of the obtained plurality of points-of-interest; electronically determines a mindset function from a plurality of mindset functions, the mindset function including a predefined function; electronically determines a group from the plurality of groups based upon the information about the obtained plurality of points-of-interest and the determined mindset function; and communic

Abstract: A method for automatically generating, in real-time, for display on a display, a simplified network layout from an initial network layout including one or more lines each connecting a plurality of nodes. Graph information is provided indicating vertices representing geographic positions of the nodes and edges representing connections between the nodes. The nodes are repositioned to optimize an objective function based on readability of the simplified network layout. Nodes and edges are discretized using interpolation to align a plurality of the nodes and connect the aligned nodes using simplified k-linear segments, where k-linear segments are parallel to one of k equidistant orientations whose angles are multiples of 180/k degrees, with k larger or equal to two. The simplified network layout is provided for a display.

Abstract: A computer-implemented method for accurately and efficiently generating ambient point-of-interest recommendations electronically obtains a plurality of points-of-interest for an area, the area being an area selected by a user associated with a location of the user; electronically retrieves point-of-interest data including visitor information about visitors associated with the obtained plurality of points-of-interest and information about the obtained plurality of points-of-interest; electronically forms a plurality of groups based upon the visitor information, each group of the plurality of groups being associated with a point-of-interest of the obtained plurality of points-of-interest; electronically determines a mindset function from a plurality of mindset functions, the mindset function including a predefined function; electronically determines a group from the plurality of groups based upon the information about the obtained plurality of points-of-interest and the determined mindset function; and communic

Abstract: A computer-implemented system and method for identifying passenger trips on a transportation network are described. The method includes acquiring transaction data for a collection of passengers boarding at stops on a transportation network. The network includes a plurality of routes. Route sequences are identified, based on the transaction data, each route sequence including at least two trip segments by a passenger. Each pair of trip segments of an identified route sequence are spaced by a transfer. For each identified route sequence, using a trip planner, the route sequence is classified as a multi-segment trip that includes at least one transfer or a multi-trip journey. A route sequence which is classified as a multi-trip journey is partitioned into at least two trips, each trip being a multi-segment trip or a single-segment trip.

Abstract: A system and method are provided for predicting passenger loads at vehicle stops on a transportation network. The method includes providing a classifier which has been trained to predict passenger loads at vehicle stops on a transportation route, based on reconstructed passenger loads for vehicle stops on the route. Transaction data is acquired for passengers boarding at vehicle stops on the transportation route. Reconstructed passenger loads are computed for vehicle stops on the route based on the transaction data. With the trained classifier, a passenger load for at least one of the vehicle stops on the transportation route is predicted, based on the reconstructed passenger load for the vehicle stop.

Abstract: A computer-implemented system and method for identifying passenger trips on a transportation network are described. The method includes acquiring transaction data for a collection of passengers boarding at stops on a transportation network. The network includes a plurality of routes. Route sequences are identified, based on the transaction data, each route sequence including at least two trip segments by a passenger. Each pair of trip segments of an identified route sequence are spaced by a transfer. For each identified route sequence, using a trip planner, the route sequence is classified as a multi-segment trip that includes at least one transfer or a multi-trip journey. A route sequence which is classified as a multi-trip journey is partitioned into at least two trips, each trip being a multi-segment trip or a single-segment trip.

Abstract: Methods and systems for interpretable user behavior profiling in off-street parking applications. To render user profiles easy to interpret by decision makers, the semi-automatic discovery and tagging of user profiles can be implemented. Transaction data from one or more (and geographically close) off-street parking installations can be implemented. An analysis of spatio-temporal behavioral patterns can be implemented based on representation of any parking episode by a set of heterogeneous features, the use of clustering methods for automatic pattern discovery, an assessment of obtained clusters, semi-automatic identification/tagging of space-temporal patterns, and a user-friendly interpretation of obtained patterns.

Abstract: A computer-implemented system and method generate a representation of travel costs for an individual traveler. The method includes computing a fixed community cost component attributable to each traveler in a community, per time period, computing a fixed individual cost component for the individual traveler, per time period, and for each of a set of time periods, computing a variable individual cost component for the individual traveler. For each of the time periods in the set of time periods, the fixed community cost, fixed individual cost, and variable individual cost components are aggregated into an aggregated cost. A representation is generated for displaying the aggregated costs for the set of time periods to the individual traveler, in which the three cost components are identified.

Abstract: A method and system are disclosed for learning a demand model and simulation parameters from validation information. Validation information is received from automatic fare collection systems and trips are reconstructed from the validation information. Origins, destinations, and arrival/departure times are estimated from the reconstructed trips. A demand model is then generated from the origins, destinations, and times. Assignment model parameters are then learned from the received validation information and demand model via iterative simulations. Infrastructure changes are made to a simulated transportation network based on the assignment and demand model using the learned parameters. A simulated response of the transportation network to the infrastructure change is then output.

Abstract: A method for authentication of user reviews includes providing a user certificate to a user's mobile device. A transaction log is received from the mobile device. The transaction log includes an encrypted tag identifier which has been transmitted to the mobile device from a review tag at a location where a service is provided by a service provider when the review tag has verified the validity of the user certificate. The encrypted tag identifier is decrypted to identify the service provider. The user is prompted to submit a review of the service provided by the service provider.

Abstract: A method and system are disclosed for wireless payment and information collection. A central system generates a personalized application including unique application and transaction identifiers, security keys, and signatures for a user device. The user device implements the personalized application in order to access the services of the associated network. Tags, capable of short-range communication with the user devices, are deployed to service access points of the associated network. The tags and user device mutually authenticate and share identifiers. Validation of the user device results in the tag updating an irreversible counter, generating transaction certificate, and logging this transaction information. The transaction certificate and a portion of the log are communicated to the user device, and service is granted. The user device transmits the transaction information and log to the central system for billing when a network connection is available.

Abstract: A method for computing a metric for evaluating reliability of a transportation service includes collecting transportation data for at least a part of a transportation network. For at least one of the stops on at least one route of the network, dimensions of the metric for evaluating reliability are computed. The dimensions are selected from: a) a perceived waiting cost, b) a cost of lateness at a final destination, based on a difference between a scheduled arrival time and an actual arrival time; and c) an annoyance cost due to a missed connection at the stop. A representation of at least one of the computed dimensions is generated for at least one of the stops, for at least one of the passengers and is output.

Abstract: A method for mobility demand modeling uses passenger demand data and geographical data for a transportation network. The demand data includes, for each of a plurality of stops in the transportation network, a passenger demand for each of a plurality of time intervals. The geographical data includes, for each of the plurality of stops in the transportation network, geographical features representing local points-of-interest. A dependence between the demand data and the geographical data is modeled by learning first and second mapping functions for embedding the demand data and the geographical data into the same latent space. The first and second mapping functions are learnt so as to optimize a correlation between the passenger demand data and the geographic data in the latent space. From the model, a prediction of passenger demand or of local point of interest for a proposed stop in the transport network can be generated.

Abstract: Methods and systems for modeling user arrival and choice in the context of off-street parking solutions. A first component models the arrival and duration of stay of users as a function of time, taking into account different user profiles (or “clusters”), captured by a latent variable. A second component provides a ranking function (for each user cluster), wherein the input features describing the “choice” constitute status variables associated different car park(s), and the output constitutes a preferred car park and a pricing scheme. The system simulates different user behaviors by assuming some standard groups of users will behave similarly. Groups of users or user profiles are learned automatically. The profiles are then employed as a key element for automatically learning a decision function of parking users, and automatically learning one decision function per profile.

Abstract: An alert processing system and method are adapted for processing device alerts. The system includes a routing device in communication with a printer. The routing device receives at least one alert description in a source language transmitted from the printer. The routing device identifies a set of words derived from the alert description related to a condition of the associated device. The routing device compares the set of words, in a target language, to a categorization model and, based on the comparison, categorizes the set of words into to one of a predetermined set of alert categories.

Abstract: A system and method for guiding a user in building a query are disclosed. The method includes providing an interaction space in which a user formulates a query using a plurality of query building blocks selected from a predefined set of query building blocks. The user's formulation of the query is guided. Guiding selection of at least a next building block is provided by at least one of a content-based mechanism which limits the selection of the next building block to those which will yield at least one result from an indexed collection of documents, a structure-based selection mechanism which limits the selection of the next building block to those which meet a predefined grammar, and a usage-based selection mechanism which proposes a next building block based on patterns of building blocks used in building prior queries. Each of these guidance mechanisms may be provided with the result that the next block proposed is informed by each of the mechanisms.

Abstract: A method, non-transitory computer readable medium, and apparatus for predicting a location of a short text are disclosed. For example, the method trains a model for each parent node of a grid of a plurality of parent nodes of a geographical area using a plurality of previously received short texts having a known location, receives the short text, applies a hierarchical modeling algorithm to the short text to calculate a weighted probability for one or more child nodes of one or more of the plurality of parent nodes and predicts the location of the short text within the grid of the geographical area based upon a child node of the one or more child nodes having a highest weighted probability.

Abstract: A method and system are disclosed for learning a demand model and simulation parameters from validation information. Validation information is received from automatic fare collection systems and trips are reconstructed from the validation information. Origins, destinations, and arrival/departure times are estimated from the reconstructed trips. A demand model is then generated from the origins, destinations, and times. Assignment model parameters are then learned from the received validation information and demand model via iterative simulations. Infrastructure changes are made to a simulated transportation network based on the assignment and demand model using the learned parameters. A simulated response of the transportation network to the infrastructure change is then output.