Abstract: Disclosed herein are methods and systems for generating automatically transactional dialog flows for a virtual assistant based on a set of predefined (labeled) transactional flows defining user interaction paths to accomplish one or more tasks. The virtual assistant is represented by a tree structure comprising a plurality of dialog nodes where each transactional flow comprises a respective subset of the nodes descending from a parent node to one or more completion nodes. New transactional flows may be generated automatically based on similarity with the predefined transactional flows, by selecting a candidate node and one of the predefined transactional flows comprising a completion node most similar to the candidate completion node and further selecting a candidate parent node most similar to the parent node of the selected predefined transactional flow. The new transactional flows may be then generated to comprise all descendant nodes of the candidate parent node.

Abstract: An example system includes a processor that can receive conversation logs of a dialogue system to be analyzed. The processor can train a predictive machine learning model using a training set of the conversation logs on a selected feature to obtain feature values with associated importance values. The processor can select a number of feature values using a significance score calculated based on the associated importance values. The processor can generate an interactive user interface including the selected number of feature values.

Abstract: An example system includes a processor that can receive conversation logs of a dialogue system to be analyzed. The processor can train a predictive machine learning model using a training set of the conversation logs on a selected feature to obtain feature values with associated importance values. The processor can select a number of feature values using a significance score calculated based on the associated importance values. The processor can generate an interactive user interface including the selected number of feature values.

Abstract: Disclosed herein are methods and systems for generating automatically transactional dialog flows for a virtual assistant based on a set of predefined (labeled) transactional flows defining user interaction paths to accomplish one or more tasks. The virtual assistant is represented by a tree structure comprising a plurality of dialog nodes where each transactional flow comprises a respective subset of the nodes descending from a parent node to one or more completion nodes. New transactional flows may be generated automatically based on similarity with the predefined transactional flows, by selecting a candidate node and one of the predefined transactional flows comprising a completion node most similar to the candidate completion node and further selecting a candidate parent node most similar to the parent node of the selected predefined transactional flow. The new transactional flows may be then generated to comprise all descendant nodes of the candidate parent node.

Abstract: A system for managing medical events, includes: at least one medical sensor, configured to output a plurality of sensor measurements; at least one display; at least one hardware processor connected to the medical sensor and the display, and adapted to: receive a plurality of events, each having a time of occurrence, including the plurality of measurements and a plurality of external events; identify a target sequence of events in the plurality of events; identify in the plurality of events a plurality of matching sequences, each including a sequence of events matching the target sequence; augment each of the matching sequences with some temporally related events according to a predefined time test; cluster the plurality of augmented sequences in a plurality of clusters according to a temporal distribution of events; and display on the display a visual representation of the plurality of clusters according to a predefined set of similarity criteria.

Abstract: A system including: A main virtual assistant (VA) that is configured to operate a back-end system according to instructions. An intermediary VA that is configured to: learn, by conversing with the human user and by analyzing responses from the main VA to the human user, to perform a task that is associated with the back-end system; hold a conversation with the main VA, wherein, in the conversation, the instructions are formulated and relayed from the intermediary VA to the main VA based on the learning and on further conversing with the human user, such that the main VA operates the back-end system according to the instructions; and formulate and relay responses to the instructions from the main VA to the human user.

Abstract: A pathway for each entity in a cohort may be extracted from raw data comprising a plurality of events. A common graph structure may be created based the extracted pathways. For each cohort, a relative signature trait may be computed for each edge based on a number of appearances of the edge in the extracted pathways that are associated with the cohort. A relationship expression may be obtained. The relationship expression may be with respect to at least two cohorts for which relative signature traits were computed. The common graph structure may be processed based on the relationship expression to determine an output label for each edge. A visualization of the common graph structure may be displayed.

Abstract: There is provided a method of creating a cohort clinical pathway graph based on knowledge-driven manual user input and automated data-driven mining comprising: receiving via a graphical user interface (GUI), manual selections including: knowledge-driven variable(s) denoting clinically significant values representing elements of a clinical decision making process, and an anchoring location of each knowledge-driven node denoting a respective knowledge-drive variable within a directed acyclic graph (DAG), computing individual clinical pathways for each of the sampled population of patients by automatically computing data-driven nodes denoting the data-driven discovery of event types relative to the manual selections, and aggregating the individual clinical pathways to compute a cohort clinical pathway DAG, wherein the cohort clinical pathway DAG includes nodes comprising the knowledge-driven nodes, the data-driven nodes, and links connecting the nodes, each link denoting an automatically discovered sequence betw

Abstract: A pathway for each entity in a cohort may be extracted from raw data comprising a plurality of events. A common graph structure may be created based the extracted pathways. For each cohort, a relative signature trait may be computed for each edge based on a number of appearances of the edge in the extracted pathways that are associated with the cohort. A relationship expression may be obtained. The relationship expression may be with respect to at least two cohorts for which relative signature traits were computed. The common graph structure may be processed based on the relationship expression to determine an output label for each edge. A visualization of the common graph structure may be displayed.

Abstract: There is provided a method of creating a cohort clinical pathway graph based on knowledge-driven manual user input and automated data-driven mining comprising: receiving via a graphical user interface (GUI), manual selections including: knowledge-driven variable(s) denoting clinically significant values representing elements of a clinical decision making process, and an anchoring location of each knowledge-driven node denoting a respective knowledge-drive variable within a directed acyclic graph (DAG), computing individual clinical pathways for each of the sampled population of patients by automatically computing data-driven nodes denoting the data-driven discovery of event types relative to the manual selections, and aggregating the individual clinical pathways to compute a cohort clinical pathway DAG, wherein the cohort clinical pathway DAG includes nodes comprising the knowledge-driven nodes, the data-driven nodes, and links connecting the nodes, each link denoting an automatically discovered sequence betw

Abstract: A system for managing medical events, includes: at least one medical sensor, configured to output a plurality of sensor measurements; at least one display; at least one hardware processor connected to the medical sensor and the display, and adapted to: receive a plurality of events, each having a time of occurrence, including the plurality of measurements and a plurality of external events; identify a target sequence of events in the plurality of events; identify in the plurality of events a plurality of matching sequences, each including a sequence of events matching the target sequence; augment each of the matching sequences with some temporally related events according to a predefined time test; cluster the plurality of augmented sequences in a plurality of clusters according to a temporal distribution of events; and display on the display a visual representation of the plurality of clusters according to a predefined set of similarity criteria.

Abstract: Automatic determination of presence-related roles. Presence data of a plurality of users in a space comprised of one or more zones is received. For each user of the plurality of users a value of a target metric in a zone is computed based on the presence data, the target metric defining a measure of user presence. A presence-related role is assigned to a user with respect to the zone, the presence-related role being comprised in a set of one or more presence-related roles describing categories of spatiotemporal occupancy relation between the user and the zone, wherein said assigning comprises applying a mapping function on the value, the mapping function maps between values of the target metric and the one or more presence-related roles, the mapping function is affected by analytics of the presence data.

Abstract: Automatic determination of presence-related roles. Presence data of a plurality of users in a space comprised of one or more zones is received. For each user of the plurality of users a value of a target metric in a zone is computed based on the presence data, the target metric defining a measure of user presence. A presence-related role is assigned to a user with respect to the zone, the presence-related role being comprised in a set of one or more presence-related roles describing categories of spatiotemporal occupancy relation between the user and the zone, wherein said assigning comprises applying a mapping function on the value, the mapping function maps between values of the target metric and the one or more presence-related roles, the mapping function is affected by analytics of the presence data.

Abstract: A method and system for generating a map using a computer is based on data and weighted factors to minimize corresponding projection distortions. The method and system includes determining visualization goals from analyzing a set of datasets for a map using the computer. A set of visualization characteristics are calculated for each dataset based on the visualization goals using the computer. The visualization characteristics are analyzed to weight factors for each of the datasets. Each of the weighted factors is adjusted based on the relevance of each of the datasets for visualization of the map. An aggregate vector of weighted factors is calculated based on all of the datasets, and the map for visualization is generated based on the aggregate vector of weighted factors.

Abstract: A method and system for generating a map using a computer is based on data and weighted factors to minimize corresponding projection distortions. The method and system includes determining visualization goals from analyzing a set of datasets for a map using the computer. A set of visualization characteristics are calculated for each dataset based on the visualization goals using the computer. The visualization characteristics are analyzed to weight factors for each of the datasets. Each of the weighted factors is adjusted based on the relevance of each of the datasets for visualization of the map. An aggregate vector of weighted factors is calculated based on all of the datasets, and the map for visualization is generated based on the aggregate vector of weighted factors.

Abstract: A method and system for generating a map using a computer is based on data and weighted factors to minimize corresponding projection distortions. The method and system includes determining visualization goals from analyzing a set of datasets for a map using the computer. A set of visualization characteristics are calculated for each dataset based on the visualization goals using the computer. The visualization characteristics are analyzed to weight factors for each of the datasets. Each of the weighted factors is adjusted based on the relevance of each of the datasets for visualization of the map. An aggregate vector of weighted factors is calculated based on all of the datasets, and the map for visualization is generated based on the aggregate vector of weighted factors.

Abstract: A method and system for generating a map using a computer is based on data and weighted factors to minimize corresponding projection distortions. The method and system includes determining visualization goals from analyzing a set of datasets for a map using the computer. A set of visualization characteristics are calculated for each dataset based on the visualization goals using the computer. The visualization characteristics are analyzed to weight factors for each of the datasets. Each of the weighted factors is adjusted based on the relevance of each of the datasets for visualization of the map. An aggregate vector of weighted factors is calculated based on all of the datasets, and the map for visualization is generated based on the aggregate vector of weighted factors.

Abstract: A method and system for generating a map using a computer is based on data and weighted factors to minimize corresponding projection distortions. The method and system includes determining visualization goals from analyzing a set of datasets for a map using the computer. A set of visualization characteristics are calculated for each dataset based on the visualization goals using the computer. The visualization characteristics are analyzed to weight factors for each of the datasets. Each of the weighted factors is adjusted based on the relevance of each of the datasets for visualization of the map. An aggregate vector of weighted factors is calculated based on all of the datasets, and the map for visualization is generated based on the aggregate vector of weighted factors.

Abstract: A method and system for generating a map using a computer is based on data and weighted factors to minimize corresponding projection distortions. The method and system includes determining visualization goals from analyzing a set of datasets for a map using the computer. A set of visualization characteristics are calculated for each dataset based on the visualization goals using the computer. The visualization characteristics are analyzed to weight factors for each of the datasets. Each of the weighted factors is adjusted based on the relevance of each of the datasets for visualization of the map. An aggregate vector of weighted factors is calculated based on all of the datasets, and the map for visualization is generated based on the aggregate vector of weighted factors.

Abstract: Methods, computing systems and computer program products implement embodiments of the present invention that include receiving, by a computer, signals from a multiplicity of independently operated mobile entities, and identifying, based on the received signals, a collaboration between a first given entity and a second given entity. Based on the received signals, a quality of the collaboration can be computed.