Abstract: A method uses natural language for visual analysis of a dataset. A data visualization application displays a data visualization, at a computer, based on a dataset retrieved from a database using a set of one or more queries. A user specifies a natural language command related to the displayed data visualization, and the computer extracts an analytic phrase from the natural language command. The computer computes semantic relatedness between the analytic phrase and numeric data fields in the dataset. The computer identifies numeric data fields having highest semantic relatedness to the analytic phrase, and also selects a relevant numerical function. The numerical function compares data values in the numeric data fields to a threshold value. The computer retrieves an updated dataset that filters the identified numeric data fields according to the numeric function. The computer then displays an updated data visualization using the updated dataset.

Abstract: A method uses natural language for visual analysis of a dataset, and is performed at a computer having a display, processors, and memory. The computer displays a data visualization based on a dataset retrieved from a database and receives a first user input to specify a natural language command related to the displayed data visualization. Based on the displayed data visualization and the natural language command, the computer identifies an initial range of values for a first data field in the dataset and displays an editable user interface control showing the initial range of values. The computer receives a second user input, at the user interface control, specifying a modified range of values for the first data field and retrieves an updated dataset from the database using the modified range of values for the first data field. The computer then updates the displayed data visualization using the updated dataset.

Abstract: A method utilizes data discovery to support visual analysis of datasets. A user selects a data source, and the method presents a natural language interface for analysis of the data source. A user specifies an incomplete natural language command directed to the data source, and the method correlates words in the incomplete natural language command with a data field in the data source. The method determines the data type of the data field and a range of data values for the data field. According to the data type and the range of data values, the method presents one or more autocompletion options for the incomplete natural language command. Each option includes respective text and a respective corresponding visual graphic. The user selects one of the autocompletion options, and the method forms a complete natural language command. The method then displays a data visualization according to the complete natural language command.

Abstract: A method and device for automatic meeting detection and analysis. A mobile electronic device includes multiple sensors configured to selectively capture sensor data. A classifier is configured to analyze the sensor data to detect a meeting zone for a meeting with multiple participants. A processor device is configured to control the multiple sensors and the classifier to trigger sensor data capture.

Abstract: A method uses natural language for visual analysis of a dataset, and is performed at a computer having a display, processors, and memory. The computer displays a data visualization based on a dataset retrieved from a database and receives a first user input to specify a natural language command related to the displayed data visualization. Based on the displayed data visualization and the natural language command, the computer identifies an initial range of values for a first data field in the dataset and displays an editable user interface control showing the initial range of values. The computer receives a second user input, at the user interface control, specifying a modified range of values for the first data field and retrieves an updated dataset from the database using the modified range of values for the first data field. The computer then updates the displayed data visualization using the updated dataset.

Abstract: A method uses natural language for visual analysis of a dataset, and is performed at a computer having a display, processors, and memory. The computer displays a data visualization based on a dataset retrieved from a database and receives a first user input to specify a natural language command related to the displayed data visualization. Based on the displayed data visualization and the natural language command, the computer identifies an initial range of values for a first data field in the dataset and displays an editable user interface control showing the initial range of values. The computer receives a second user input, at the user interface control, specifying a modified range of values for the first data field and retrieves an updated dataset from the database using the modified range of values for the first data field. The computer then updates the displayed data visualization using the updated dataset.

Abstract: A method utilizes data discovery to support visual analysis of datasets. A user selects a data source, and the method presents a natural language interface for analysis of the data source. A user specifies an incomplete natural language command directed to the data source, and the method correlates words in the incomplete natural language command with a data field in the data source. The method determines the data type of the data field and a range of data values for the data field. According to the data type and the range of data values, the method presents one or more autocompletion options for the incomplete natural language command. Each option includes respective text and a respective corresponding visual graphic. The user selects one of the autocompletion options, and the method forms a complete natural language command. The method then displays a data visualization according to the complete natural language command.

Abstract: A method uses natural language for visual analysis of a dataset. A data visualization application displays a data visualization, at a computer, based on a dataset retrieved from a database using a set of one or more queries. A user specifies a natural language command related to the displayed data visualization, and the computer extracts an analytic phrase from the natural language command. The computer computes semantic relatedness between the analytic phrase and numeric data fields in the dataset. The computer identifies numeric data fields having highest semantic relatedness to the analytic phrase, and also selects a relevant numerical function. The numerical function compares data values in the numeric data fields to a threshold value. The computer retrieves an updated dataset that filters the identified numeric data fields according to the numeric function. The computer then displays an updated data visualization using the updated dataset.

Abstract: A method uses natural language for visual analysis of a dataset. The method displays a data visualization based on a first dataset. The method then extracts analytic phrases from a first natural language command related to the data visualization. The method computes conversation centers associated with the first natural language command based on the analytic phrases and computes analytical functions for the conversation centers, thereby creating functional phrases. The method updates the data visualization based on the functional phrases. The method extracts new analytic phrases from a second natural language command related to the updated data visualization and computes a temporary conversation centers associated with the second natural language command based on the new analytic phrases. The method derives new conversation centers from the original conversation centers and the temporary conversation centers using transitional rules.

Abstract: A method uses natural language for visual analysis of a dataset. A data visualization is displayed based on a first dataset. The method then extracts analytic phrases from a natural language command related to the data visualization. The method computes conversation centers based on the analytic phrases and computes analytical functions associated with the conversation centers, thereby creating functional phrases. The method updates the data visualization according to the functional phrases. The method then extracts analytic phrases from a second natural language command related to the updated data visualization, and computes temporary conversation centers from these analytic phrases. The method then computes cohesion between the first analytic phrases and the second analytic phrases to build a set of conversation centers, and computes analytical functions from this set of conversation centers, thereby creating functional phrases.

Abstract: A method uses natural language processing for visual analysis of a dataset by a computer. The computer displays a data visualization based on a dataset retrieved from a database using a set of one or more queries. The computer receives user input (e.g., keyboard or voice) to specify a natural language command related to the displayed data visualization. Based on the displayed data visualization, the computer extracts one or more independent analytic phrases from the natural language command. The computer further computes semantic relatedness of extracted analytic phrases, and computes analytical functions associated with the extracted analytic phrases, thereby creating functional phrases. The computer requeries the database using an updated set of one or more queries based on the created functional phrases, thereby retrieving an updated dataset. The computer then displays an updated data visualization using the updated dataset.

Abstract: A method uses natural language processing for visual analysis of a dataset by a computer. The computer displays a data visualization based on a dataset retrieved from a database using a first set of database queries. The computer receives user input (e.g., keyboard or voice) to specify a natural language command related to the displayed data visualization. Based on the displayed data visualization, the computer extracts one or more independent analytic phrases from the natural language command. The computer further computes a set of conversation centers associated with the natural language command based on the set of one or more analytic phrases. The computer then computes a set of analytical functions associated with the set of one or more conversation centers, thereby creating a set of one or more functional phrases. The device then updates the data visualization based on the set of one or more functional phrases.

Abstract: Method, apparatus and system for determining a wearing position of a wearable device. The method includes receiving motion data from a wearable device associated with an individual, wherein the motion data comprises a first data segment and a second data segment, the first data segment associated with walking, and the second data segment associated with non-walking. The method further includes determining first characteristic data associated with the first data segment and second characteristic data associated with the second data segment. The method further includes determining, by a computing device, a wearing position of the wearable device associated with the individual based on the first characteristic data and a match between the second characteristic data and an activity signature associated with a time of day.

Abstract: A method of using natural language processing for visual analysis of a data set includes displaying a data visualization based on a dataset retrieved from a database using a set of one or more queries and receiving a user input to specify a natural language command related to the displayed data visualization. The method further includes, based on the displayed data visualization, extracting one or more independent analytic phrases from the natural language command. The method further includes requerying the database using an updated set of one or more queries based on the extracted analytic phrases, thereby retrieving an updated dataset and displaying an updated data visualization using the updated dataset.

Abstract: The present application relates to sensors and methods for detecting and/or quantifying an oxidant such as free chlorine in a liquid sample such as drinking water. The sensors comprise a first electrode, a second electrode and a composite material between and connecting the first electrode and the second electrode, the composite material comprising a semiconductor and a redox-switchable organic compound associated therewith. The methods comprise exposing the liquid sample to the sensor under conditions to oxide the redox-switchable organic compound and analyzing a resulting change in current.

Abstract: Method, apparatus and system for determining a wearing position of a wearable device. The method includes receiving motion data from a wearable device associated with an individual, wherein the motion data comprises a first data segment and a second data segment, the first data segment associated with walking, and the second data segment associated with non-walking. The method further includes determining first characteristic data associated with the first data segment and second characteristic data associated with the second data segment. The method further includes determining, by a computing device, a wearing position of the wearable device associated with the individual based on the first characteristic data and a match between the second characteristic data and an activity signature associated with a time of day.

Abstract: A method and device for automatic semantic labeling of unlabeled places using activity recognition. A method includes determining at least one activity based on analyzing electronic device sensor data. Localization for the electronic device is performed to determine location for an unknown semantic place. An observed mapping between the at least one activity and the location for the unknown semantic place is determined. A typical mapping between the at least one activity and at least one semantic place is determined. Using the observed mapping and the typical mapping from one or more other electronic devices, the unknown semantic place is assigned with a semantic place label representing the at least one semantic place for identifying the unknown semantic place. A semantic place map is updated to include the semantic place label.

Abstract: A method and device for automatic semantic labeling of unlabeled places using activity recognition. A method includes determining at least one activity based on analyzing electronic device sensor data. Localization for the electronic device is performed to determine location for an unknown semantic place. An observed mapping between the at least one activity and the location for the unknown semantic place is determined. A typical mapping between the at least one activity and at least one semantic place is determined. Using the observed mapping and the typical mapping from one or more other electronic devices, the unknown semantic place is assigned with a semantic place label representing the at least one semantic place for identifying the unknown semantic place. A semantic place map is updated to include the semantic place label.

Abstract: A method and device for automatic meeting detection and analysis. A mobile electronic device includes multiple sensors configured to selectively capture sensor data. A classifier is configured to analyze the sensor data to detect a meeting zone for a meeting with multiple participants. A processor device is configured to control the multiple sensors and the classifier to trigger sensor data capture.

Abstract: The present application relates to sensors and methods for detecting and/or quantifying an oxidant such as free chlorine in a liquid sample such as drinking water. The sensors comprise a first electrode, a second electrode and a composite material between and connecting the first electrode and the second electrode, the composite material comprising a semiconductor and a redox-switchable organic compound associated therewith. The methods comprise exposing the liquid sample to the sensor under conditions to oxide the redox-switchable organic compound and analyzing a resulting change in current.