Abstract: A method, system and computer program product for assessing similarity between two job description documents. Job description documents consist of sentences framed in a particular manner, where the sentences are represented as a set of actions, an object corresponding to each action and a set of attributes corresponding to the object. The two job description documents are parsed to generate a first and a second set of an action-object-attribute triplet representation, where the first set of the action-object-attribute triplet representation is associated with the first job description document and the second set of the action-object-attribute triplet representation is associated with the second job description document. A similarity score between the first and second sets of action-object-attribute triplet representations is then calculated by hierarchically matching the first and second sets of action-object-attribute triplet representations across the job description documents.

Abstract: A method, system and computer program product for assessing similarity between two job description documents. Job description documents consist of sentences framed in a particular manner, where the sentences are represented as a set of actions, an object corresponding to each action and a set of attributes corresponding to the object. The two job description documents are parsed to generate a first and a second set of an action-object-attribute triplet representation, where the first set of the action-object-attribute triplet representation is associated with the first job description document and the second set of the action-object-attribute triplet representation is associated with the second job description document. A similarity score between the first and second sets of action-object-attribute triplet representations is then calculated by hierarchically matching the first and second sets of action-object-attribute triplet representations across the job description documents.

Abstract: Aspects of the present invention disclose a method, executed by a computer, for generating retailing analytics. The method includes receiving a spatial map corresponding to an environment. The method further includes receiving, from a purchasable item comprising one or more textile-integrated sensors, sensor information The purchasable item is located in the environment. The method further includes analyzing the sensor information to produce retail analytics corresponding to the purchasable item. The method further includes and sending the retail analytics to a client device. A computer program product and computer system corresponding to the above method are also disclosed herein.

Abstract: Camera settings are managed. A candidate subject for capture by a camera is detected. The detection is based on historical profile data related to a user of the camera. One or more adjustments of the camera are identified for capture of the candidate subject. The one or more adjustments are identified based on the detected candidate subject. A proper capture action is performed based on the identified adjustments.

Abstract: Camera settings are managed. A candidate subject for capture by a camera is detected. The detection is based on historical profile data related to a user of the camera. One or more adjustments of the camera are identified for capture of the candidate subject. The one or more adjustments are identified based on the detected candidate subject. A proper capture action is performed based on the identified adjustments.

Abstract: A method, system and computer program product for assessing similarity between two job description documents. Job description documents consist of sentences framed in a particular manner, where the sentences are represented as a set of actions, an object corresponding to each action and a set of attributes corresponding to the object. The two job description documents are parsed to generate a first and a second set of an action-object-attribute triplet representation, where the first set of the action-object-attribute triplet representation is associated with the first job description document and the second set of the action-object-attribute triplet representation is associated with the second job description document. A similarity score between the first and second sets of action-object-attribute triplet representations is then calculated by hierarchically matching the first and second sets of action-object-attribute triplet representations across the job description documents.

Abstract: A computer-implemented method for detecting and ranking individuals includes capturing live image data of a scene using an imaging device and identifying overlap between reference image data of the selected individuals and the live image data, wherein the overlap includes image data of the selected individuals in the scene. The method also includes capturing sets of image data of the selected individuals while the imaging device is in motion and recording the movement to provide a tracking record having instructions for positioning the imaging device where the imaging device captured the sets of image data of the selected individuals in the scene. The method further includes determining a score for each of the selected individuals in the scene based on a value related to an ability to view each friend and/or a social relationship value in order to enable a user to select who to aim the imaging device at.

Abstract: A computer-implemented method for detecting and ranking individuals includes capturing live image data of a scene using an imaging device and identifying overlap between reference image data of the selected individuals and the live image data, wherein the overlap includes image data of the selected individuals in the scene. The method also includes capturing sets of image data of the selected individuals while the imaging device is in motion and recording the movement to provide a tracking record having instructions for positioning the imaging device where the imaging device captured the sets of image data of the selected individuals in the scene. The method further includes determining a score for each of the selected individuals in the scene based on a value related to an ability to view each friend and/or a social relationship value in order to enable a user to select who to aim the imaging device at.

Abstract: Camera settings are managed. A candidate subject for capture by a camera is detected. The detection is based on historical profile data related to a user of the camera. One or more adjustments of the camera are identified for capture of the candidate subject. The one or more adjustments are identified based on the detected candidate subject. A proper capture action is performed based on the identified adjustments.

Abstract: A method, executed by a computer, for generating retailing analytics includes receiving a spatial map corresponding to an environment, receiving, from a purchasable item comprising one or more textile-integrated sensors, sensor information, wherein the purchasable item is located in the environment, analyzing the sensor information to produce retail analytics corresponding to the purchasable item, and sending the retail analytics to a client device. A computer program product and computer system corresponding to the above method are also disclosed herein.

Abstract: A computer-implemented method for detecting and ranking individuals includes capturing live image data of a scene using an imaging device and identifying overlap between reference image data of the selected individuals and the live image data, wherein the overlap includes image data of the selected individuals in the scene. The method also includes capturing sets of image data of the selected individuals while the imaging device is in motion and recording the movement to provide a tracking record having instructions for positioning the imaging device where the imaging device captured the sets of image data of the selected individuals in the scene. The method further includes determining a score for each of the selected individuals in the scene based on a value related to an ability to view each friend and/or a social relationship value in order to enable a user to select who to aim the imaging device at.

Abstract: A computer-implemented method for detecting and ranking individuals includes capturing live image data of a scene using an imaging device and identifying overlap between reference image data of the selected individuals and the live image data, wherein the overlap includes image data of the selected individuals in the scene. The method also includes capturing sets of image data of the selected individuals while the imaging device is in motion and recording the movement to provide a tracking record having instructions for positioning the imaging device where the imaging device captured the sets of image data of the selected individuals in the scene. The method further includes determining a score for each of the selected individuals in the scene based on a value related to an ability to view each friend and/or a social relationship value in order to enable a user to select who to aim the imaging device at.

Abstract: A computer-implemented method includes: determining, by a computing device, mood states of one or more individuals within an observation zone over a period of time based on audio data received from one or more audio input devices implemented within the observation zone; determining, by the computing device, a deviation between the mood states and expected mood states; generating, by the computing device, a model representing the deviation; and providing, by the computing device, a visual representation of the model.