Abstract: A method includes electronically receiving at a user device of a second party a digital promise to pay a certain amount of money in exchange for goods or services from the second party, the digital promise to pay being generated by a user device of a first party; electronically sending a request from the user device of the second party to a user device of a third party to electronically transfer the digital promise to pay to the user device of the third party in exchange for goods or services from the third party. Sending the request includes sending at least one set of preferences defined at least by the first party. The method further includes electronically receiving at the user device of the second party from the third party one of an acceptance or a rejection of the request to transfer the digital promise to pay.

Abstract: A method includes electronically receiving at a user device of a second party a digital promise to pay a certain amount of money in exchange for goods or services from the second party, the digital promise to pay being generated by a user device of a first party; electronically sending a request from the user device of the second party to a user device of a third party to electronically transfer the digital promise to pay to the user device of the third party in exchange for goods or services from the third party. Sending the request includes sending at least one set of preferences defined at least by the first party. The method further includes electronically receiving at the user device of the second party from the third party one of an acceptance or a rejection of the request to transfer the digital promise to pay.

Abstract: An aspect of this invention is a method that includes monitoring sensors to collect information for a transportation route, and generating a graph from the collected information where the graph includes a plurality of nodes, each node representing a stop on the at least one transportation route. Each of respective nodes is associated with a corresponding transportation stop density and a corresponding passenger leaving rate. The corresponding transportation stop density is compared with at least one predetermined density threshold and the corresponding passenger leaving rate is compared with at least one predetermined leaving rate threshold to determine a level of dissatisfaction for each of the respective nodes. A tangible output is generated that identifies a level of user dissatisfaction for each of the plurality of nodes.

Abstract: A method includes electronically receiving at a user device of a second party a digital promise to pay a certain amount of money in exchange for goods or services from the second party, the digital promise to pay being generated by a user device of a first party; electronically sending a request from the user device of the second party to a user device of a third party to electronically transfer the digital promise to pay to the user device of the third party in exchange for goods or services from the third party. Sending the request includes sending at least one set of preferences defined at least by the first party. The method further includes electronically receiving at the user device of the second party from the third party one of an acceptance or a rejection of the request to transfer the digital promise to pay.

Abstract: A method for surveilling a monitored environment includes classifying an individual detected in the monitored environment according to a role fulfilled by the individual within the monitored environment, generating a trajectory that illustrates movements and locations of the individual within the monitored environment, and detecting when the trajectory indicates an event that is inconsistent with an expected pattern for the role.

Abstract: An aspect of this invention is a method that includes receiving input data from an application. The input data includes information descriptive of at least one field. The method further includes processing the input data to form an array composed of legal data for the at least one field. The array is formed by merging a result of processing syntactic constraints and a result of processing semantic constraints. The method further includes outputting the array to the application. A system for performing the method is also described, as is a computer program product that can be used to execute the method.

Abstract: Embodiments focus on the real-time processing and analysis of event-related images posts on social media. By computing the most posted images and grouping them in accordance to their similarity, these images can be organized in a visual interface to provide the users an image-driven social media topic detection system. The groups of images with the highest frequency represent the most prominent topics. By keeping track of the temporal occurrence of the images, it is possible to visualize the temporal evolution of the topics.

Abstract: At least one computer processor obtains access to a relationship network and a network of a different kind than the relationship network. The at least one computer processor also obtains a user query and carries out a multiple heterogeneous networks search on the relationship network and the network of the different kind than the relationship network, by executing on the at least one computer processor a multiple heterogeneous network search module, to obtain a ranked output list responsive to the user query.

Abstract: Embodiments focus on the real-time processing and analysis of event-related images posts on social media. By computing the most posted images and grouping them in accordance to their similarity, these images can be organized in a visual interface to provide the users an image-driven social media topic detection system. The groups of images with the highest frequency represent the most prominent topics. By keeping track of the temporal occurrence of the images, it is possible to visualize the temporal evolution of the topics.

Abstract: A method for surveilling a monitored environment includes classifying an individual detected in the monitored environment according to a role fulfilled by the individual within the monitored environment, generating a trajectory that illustrates movements and locations of the individual within the monitored environment, and detecting when the trajectory indicates an event that is inconsistent with an expected pattern for the role.

Abstract: A method for surveilling a monitored environment includes classifying an individual detected in the monitored environment according to a role fulfilled by the individual within the monitored environment, generating a trajectory that illustrates movements and locations of the individual within the monitored environment, and detecting when the trajectory indicates an event that is inconsistent with an expected pattern for the role.

Abstract: A method of managing digital promises includes receiving transaction information and a request for a digital promise ranking. The transaction information includes identifying information of a first party and/or a second party. Each digital promise belongs to the first party and has a corresponding owner. A relationship score is calculated between the corresponding owner of each digital promise and the second party. An affinity score is calculated between the corresponding owner of each digital promise and the second party. A reputation score is calculated for the owner of each digital promise. A final score of each digital promise is calculated based on the relationship score, the affinity score and the reputation score. The digital promise rank is generated based on the final score of each digital promise.

Abstract: A method for surveilling a monitored environment includes classifying an individual detected in the monitored environment according to a role fulfilled by the individual within the monitored environment, generating a trajectory that illustrates movements and locations of the individual within the monitored environment, and detecting when the trajectory indicates an event that is inconsistent with an expected pattern for the role.

Abstract: A method includes electronically receiving at a user device of a second party a digital promise to pay a certain amount of money in exchange for goods or services from the second party, the digital promise to pay being generated by a user device of a first party; electronically sending a request from the user device of the second party to a user device of a third party to electronically transfer the digital promise to pay to the user device of the third party in exchange for goods or services from the third party. Sending the request includes sending at least one set of preferences defined at least by the first party. The method further includes electronically receiving at the user device of the second party from the third party one of an acceptance or a rejection of the request to transfer the digital promise to pay.

Abstract: A method of ranking workers for an incoming task includes recording a list of completed tasks in a computer data structure, extracting first attributes from the list for the tasks that were completed during a pre-determined period, generating a first feature vector for each task and worker from the first extracted attributes, training a Support Vector Machine (SVM) based on the feature vector to output a weight vector, extracting second attributes from an incoming task, generating a second feature vector for each worker based on the second extracted attributes, and ranking the workers using the second feature vectors and the weight vector. The first attributes may be updated during a subsequent period to re-train the SVM on updated first feature vectors to generate an updated weight vector. The workers may be re-ranked based on the second feature vectors and the updated weight vector. Accordingly, the feature vectors are dynamic.

Abstract: A method for surveilling a monitored environment includes classifying an individual detected in the monitored environment according to a role fulfilled by the individual within the monitored environment, generating a trajectory that illustrates movements and locations of the individual within the monitored environment, and detecting when the trajectory indicates an event that is inconsistent with an expected pattern for the role.

Abstract: A method for surveilling a monitored environment includes classifying an individual detected in the monitored environment according to a role fulfilled by the individual within the monitored environment, generating a trajectory that illustrates movements and locations of the individual within the monitored environment, and detecting when the trajectory indicates an event that is inconsistent with an expected pattern for the role.

Abstract: One embodiment of a method for detecting a lost sale due to an out-of-shelf condition in a retail environment includes automatically detecting when a customer fails to purchase an expected product, based at least in part on an observation of a current behavior of the customer in the retail environment and on a purchasing history of the customer, and inferring, based on the automatically detecting, that the expected product is out-of-shelf.

Abstract: A method for determining significant words or phrases within social media data includes receiving a stream of data from at least one social media source. The stream includes one or more words or phrases along with corresponding time stamps indicating when the word/phrase was used. One or more words/phrases to be analyzed is determined from the stream. A time period of interest is identified. The time period is divided into a plurality of non-overlapping time windows. The stream is analyzed within the time period of interest to determine how many instances of each words/phrases have timestamps within each time window. One or more of the words/phrases are identified as significant based on a level of co-occurrence of the words/phrases related to the determination as to how many instances of each words/phrases have timestamps within each window.

Abstract: A method of ranking workers for an incoming task includes recording a list of completed tasks in a computer data structure, extracting first attributes from the list for the tasks that were completed during a pre-determined period, generating a first feature vector for each task and worker from the first extracted attributes, training a Support Vector Machine (SVM) based on the feature vector to output a weight vector, extracting second attributes from an incoming task, generating a second feature vector for each worker based on the second extracted attributes, and ranking the workers using the second feature vectors and the weight vector. The first attributes may be updated during a subsequent period to re-train the SVM on updated first feature vectors to generate an updated weight vector. The workers may be re-ranked based on the second feature vectors and the updated weight vector. Accordingly, the feature vectors are dynamic.