Abstract: Methods and systems for electronic crowd-based authentication. An example embodiment includes operations or steps for selecting authentication criteria with corresponding validity criteria through a key ring application, pairing the key ring application with authentication data, and transmitting the authentication data for verification by a security server, thereby allowing a trusted user to endorse an unregistered user to provide the unregistered user with access to a secured resource by the selecting of the authentication criteria, the pairing of the key ring application, and the transmitting of the authentication data for verification by the security server.

Abstract: Method, system, and apparatus for automatic stance classification. Propositions can be collected that are relevant to a query. A classifier can classify the stance of each proposition based on whether the proposition supports the query, opposes the query, or is neutral with respect to the query in order to thereafter provide substantive data for decision making based on and extracted from the query. The stance can be classified based on, for example, an SVM-SC (SVM Based Stance Classification) approach and/or an NN-SC (Neural Network Stance Classification Approach).

Abstract: A method and a system are provided for correlation detection in multiple spatio-temporal datasets for event sensing in a geographical area. The method includes extracting datasets, comprising information about one or more events, from one or more data sources. The method further includes identifying a primary data source and secondary data sources from the one or more data sources. The method further includes extracting primary features from the datasets associated with the primary data source and secondary features from the datasets associated with the secondary data sources. The primary features are categorized into one or more categories. The method further includes training classifiers based on the primary features and/or the one or more categories. The method further includes detecting a correlation among the information associated with the one or more events based on a category transfer distribution from the primary data source to the secondary data sources.

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 computer-implemented system and method for providing guest parking reservations are provided. Motor vehicle parking spaces located in a residential area are managed through a server. Smart parking devices and vehicle occupancy sensors that are each physically proximate to least one of the parking spaces are interfaced to the server. Use of one of the parking spaces for a guest of a resident of the area is reserved. A request for a reservation is accepted and that the resident is eligible to reserve the space is confirmed. The request is granted provided the parking space is available over any other reservations in the server. Use of the parking space is managed. Occupancy of the parking space by a vehicle is sensed through the nearest sensor. An identity of a motorist is verified through the nearest parking device. The use of the parking space is denied if not by the guest.

Abstract: A method and a system for predicting admission of a human subject to a first ward in a medical center are disclosed. A patient dataset is generated based on at least a measure of one or more physiological parameters associated with one or more first human subjects and a first information pertaining to the admission of each of the one or more first human subjects to the first ward. For a first human subject of the one or more first human subjects, a first score at each of the one or more first time instants is determined. Further, one or more second time instants from the one or more first time instants are identified. Further, a second score at each of the one or more second time instants is determined. In an embodiment, the first classifier is trained based on at least the second score, and the first information.

Abstract: A system estimates quality of a digital image by accessing a corpus of digital images of one or more subjects, such as a facet of a property. The system will receive, for at least a subset of the corpus, an indicator that one or more patches of each image in the subset is out of focus. The system will train a classifier by obtaining a feature representation of each pixel in each image, along with a focus value that represents an extent to which each pixel in the image is in focus or out of focus. The system will use the classifier to analyze pixels of a new digital image and assess whether each analyzed pixel in the new digital image is in focus or out of focus. The system may use the image to assess whether an incident occurred, such as storm-related damage to the property.

Abstract: Systems, methods, and processing nodes determine and perform preventive maintenance on a transport vehicle in a transportation system. The method includes extracting features for previous incidents that have occurred to a plurality of transport vehicles in the transportation system. The method also includes determining a criticality of types of incidents based on the features extracted. The method includes predicting, based on the criticality of types of incidents and the features extracted, details of at least one future incident for a first transport vehicle from the plurality of transport vehicles. The details include a predicted type of the at least one future incident, a predicted time of the at least one future incident, and a predicted criticality of the at least one future incident. Additionally, the method includes performing a prescriptive action for the first transport vehicle to mitigate the at least one future incident in the first transport vehicle.

Abstract: A knowledge interface is provided that interacts with a user to identify a solution to a customer problem or issue with respect to a particular product or service. The knowledge interface includes data processing functionality configured to dynamically generate a number of components that are presented in at least one display window for display to the user. The components include first data identifying a set of predetermined symptoms linked to the problem or issue and related interface elements for classification of the set of predetermined symptoms, second data identifying a set of predetermined root causes linked to the set of predetermined symptoms and related interface elements for classification of the set of predetermined root causes, and third data identifying a set of solutions linked to the set of predetermined root causes. The third data identifies a best solution based upon the predetermined root causes and their associated class designations.

Abstract: According to embodiments illustrated herein, a method and a system is provided for screening candidates for job opportunities. The method includes grouping the candidates into batches based on predetermined time duration, a count of the candidates, and a chronology of receiving job applications from the candidates. Each batch comprises a first set of candidates. Thereafter, a sliding window is moved over the batches, to encompass a set of batches at a first time instance. A second set of candidates is identified from the first set of candidates in a batch from the set of batches based on a score assigned to each of the first set of candidates during an interview. Further, a candidate is selected from the second set of candidates obtained from a first batch, encompassed by the sliding window at a second time instance before the first time instance.

Abstract: Embodiments of the present invention provide a system for automatically extracting conversational structure from a voice record based on lexical and acoustic features. The system also aggregates business-relevant statistics and entities from a collection of spoken conversations. The system may infer a coarse-level conversational structure based on fine-level activities identified from extracted acoustic features. The system improves significantly over previous systems by extracting structure based on lexical and acoustic features. This enables extracting conversational structure on a larger scale and finer level of detail than previous systems, and can feed an analytics and business intelligence platform, e.g. for customer service phone calls. During operation, the system obtains a voice record. The system then extracts a lexical feature using automatic speech recognition (ASR). The system extracts an acoustic feature.

Abstract: A method and a system are provided for customer churn prediction. The method includes creating a graph comprising a plurality of nodes and a plurality of edges. At least one edge of the plurality of edges in the graph connects more than two nodes of the plurality of nodes. Each of the plurality of nodes represents a customer. Thereafter, a similarity matrix representative of a similarity between each of a plurality of customers is determined based on the graph. Further, the similarity matrix is decomposed into a first matrix and a second matrix. A third matrix is determined based on the first matrix, the second matrix, and a scaling parameter. The third matrix is utilized to identify a set of potential churn customers from the plurality of customers. Thereafter, the set of potential churn customers is presented on a user-computing device.

Abstract: A method for trip validation includes receiving signals, on a vehicle, from one of a plurality of spaced stationary beacons on a transportation route, the signals including localization data for the respective beacon. A passenger identifier is received from a mobile communication device of a passenger on the vehicle via short range communication. Encrypted transaction data is generated, based on the user identifier, localization data, and a timestamp. The encrypted transaction data is transmitted to passenger mobile communication devices which relay the data to an associated server for processing. The method allows the location of a public transportation device to be identified without the need to provide GPS localization equipment on the vehicle.

Abstract: A method for generating a visual representation of transport schedule adherence in a transit system including collecting transport schedule data received by a plurality of sensors deployed in a plurality of transit vehicles of the transit system, organizing and saving the received transport schedule data to a data storage facility, and receiving a user selection for the generation of a visual representation of transport schedule adherence in the transit system.

Abstract: What is disclosed is a system and method for forecasting and imputing an unknown vital measurement of a patient. Temporally successive patient vital measurements are received which comprise irregularly sampled observations {y1, . . . , yN}, where yj denotes the jth observation at time tj, and N is the number of samples. The vital measurements are then provided to a model trained using historical data of patient vital measurements. The model generates a parameter set ?=(A,B,C), where A is a state transition matrix, B is a control matrix, and C is a matrix which maps state-space variables to observation variables. The parameters are used to obtain state-space variable zt which, in turn, is used to forecast an unknown observation yN+1 or to impute an unknown observation yt, where 1<t<N. The historical data is then updated with the forecasted observation yN+1 or the imputed unknown observation yt.

Abstract: A computer-implemented system and method provide for mapping a set of strings onto an ontology which may be represented as a graph. The method includes receiving a set of strings, each string denoting a respective object. For each of the strings, a pairwise similarity is computed between the string and each of a set of objects in the ontology. For each of a set of candidate subsets (subgraphs) of the set of objects, a global score is computed, which is a function of the pairwise similarities between the strings and the objects in the subset and a tightness score. The tightness score is computed on the objects in the subset with a submodular function. An optimal subset is identified from the set of candidate subsets based on the global scores. Strings in the set of strings are mapped to the objects in the optimal subset, based on the pairwise similarities.

Abstract: Methods and systems are disclosed for optimizing public transportation schedules. Shifts from current schedules associated with a public transportation system can be evaluated. The impact on waiting times can then be determined, based on evaluating the shifts from the current schedules. Schedules associated with the public transportation system are then optimized based on the impact on the waiting times. Public transport schedules can thus be optimized by minimizing the waiting time during, for example, transfers. Using ticket validation data to construct a realistic scenario-based model of the waiting times, a goal of this approach is to compute shifts of the current schedules that reduce the overall expected waiting time.

Abstract: A system and method for offering customer priority parking reservations. Motor vehicle parking spaces are provided through a server. The server respectively interfaces with smart parking devices, vehicle occupancy sensors, and parking availability indicators that are each associated with the parking spaces. The parking spaces are reserved by accepting a request for a customer priority parking reservation from a merchant for a reservation period. Use of the parking space is managed through the server by activating the parking availability indicators associated with the reserved parking spaces, sensing occupancy of the parking spaces by a motor vehicle through the vehicle occupancy sensor, and retrieving and providing an identity of the driver of the motor vehicle through the nearest smart parking device to the server. The use of the parking space is validated from the merchant through the server.

Abstract: A method and a system for generating a search query to extract one or more relevant messages from a plurality of messages shared over a computer network. The method includes extracting a plurality of keywords and information pertaining to a plurality of customers from the plurality of messages. Further, the method identifies a set of influential customers from the plurality of customers based on a first score and a second score. The method further includes extracting a set of influential keywords from a first set of messages based on a first number of occurrences of the plurality of keywords in the plurality of messages within a pre-defined time interval. The method further includes generating the search query that includes at least the set of influential customers and the set of influential keywords.

Abstract: A system, method and non-transitory computer readable medium for labeling a plurality of messages from a customer-agent interaction on a social media service to identify an issue and a response are disclosed. For example, the system includes a conversation interface, a conversation database coupled to the conversation interface, a conversation analysis server coupled to the conversation database and a conversation knowledge repository coupled to the conversation analysis server. The conversation analysis server includes a preprocessing module, a dialogue act analysis module, an issue status analysis module and an issue/response identification module.