Abstract: Preventing the loss of physical objects using cognitive computing includes receiving, by a wearable device, information associated with a user of the wearable device. The information received includes one or more gestures to be used as a digital handshake and at least one physical object to be tracked. A set of models associated with the at least one physical object is downloaded to the wearable device. In response to an activation command, the wearable device performs the digital handshake with the at least one object to be tracked. The wearable device continuously monitors actions and movements performed by the user to determine whether the at least one physical object is in possession of the user.

Abstract: Embodiments of the present invention provide methods, computer program products, and systems for adapting digital content. Embodiments of the present invention can be used to identify one or more entities in media content. Embodiments of the present invention can determine that an identified entity of the one more identified entities is associated with sensitive material. Embodiments of the present invention can, in response to determining that the identified entity of the one or more identified entities is sensitive, determine a contextual impact of the identified entity. Embodiments of the present invention can also be used to modify the media content based on the determined contextual impact of the identified entity.

Abstract: An embodiment of the invention may include a method, computer program product and system for processing a natural language query. An embodiment may include receiving text of the natural language query. An embodiment may include extracting a set of features from the text through natural language processing. An embodiment may include generating a structured query based on the set of features. An embodiment may include normalizing the text to create a normalized natural language query. An embodiment may include executing a search of a corpus via the structured query and the normalized natural language query. An embodiment may include returning results of the search.

Abstract: An embodiment of the invention may include a method, computer program product and system for processing a natural language query. An embodiment may include receiving text of the natural language query. An embodiment may include extracting a set of features from the text through natural language processing. An embodiment may include generating a structured query based on the set of features. An embodiment may include normalizing the text to create a normalized natural language query. An embodiment may include executing a search of a corpus via the structured query and the normalized natural language query. An embodiment may include returning results of the search.

Abstract: Preventing the loss of physical objects using cognitive computing includes receiving, by a wearable device, information associated with a user of the wearable device. The information received includes one or more gestures to be used as a digital handshake and at least one physical object to be tracked. A set of models associated with the at least one physical object is downloaded to the wearable device. In response to an activation command, the wearable device performs the digital handshake with the at least one object to be tracked. The wearable device continuously monitors actions and movements performed by the user to determine whether the at least one physical object is in possession of the user.

Abstract: Embodiments of the present invention provide methods, computer program products, and systems for adapting digital content. Embodiments of the present invention can be used to identify one or more entities in media content. Embodiments of the present invention can determine that an identified entity of the one more identified entities is associated with sensitive material. Embodiments of the present invention can, in response to determining that the identified entity of the one or more identified entities is sensitive, determine a contextual impact of the identified entity. Embodiments of the present invention can also be used to modify the media content based on the determined contextual impact of the identified entity.

Abstract: Tracking position of at least one object in video frames. The tracking includes processing an initial frame of a set of frames, the processing the initial frame using feature extraction to identify locations of features of the at least one object. The tracking further includes using motion estimation to track locations of the features in subsequent frames of the set of frames, including iteratively performing: obtaining a next frame of the set of frames, and applying a motion estimation algorithm as between the next frame and a prior frame of the set of frames to identify updated locations of the features in the next frame, where locations of the features as identified based on the prior frame are used as input to the motion estimation algorithm to identify the updated locations of the features in the next frame based on searching less than an entirety of the next frame.

Abstract: In an approach for locating parking, a computer identifies driving directions to a destination. The computer receives a navigation input from a user to locate parking associated with the destination. The computer calculates one or more navigation paths based on the destination, wherein the one or more navigation paths include one or more street segments that connect identical starting and ending points with at least one different street segment and overall values indicating priority based on one or more weight factors associated with the one or more street segments. The computer selects a first navigation path from the calculated one or more navigation paths utilizing an ordered ranking of the one or more navigation paths. The computer provides driving directions associated with the first navigation path. The computer determines whether the user locates parking while utilizing the first navigation path.

Abstract: A not crossable element (NCE) is marked using a shape on a map. A map data does not prevent a route from crossing the NCE. A closed area is selected on the map, which includes a polygon bound on one side by a portion of the shape. A set of mapping points (MP) that are included in the closed area is selected. A route is formed by connecting one MP to another MP. A subset of MPs is identified as a set of candidate MPs (CMP). Each CMP lies within a search distance of a not-mapping point (NMP). The CMPs are sorted according to CMP-NMP distances. A subset of CMPs is selected whose paths to the NMP do not intersect with any shape corresponding to any NCE in the closed area. The NMP is linked in the route with a selected CMP from the subset of CMPs.

Abstract: Tracking position of at least one object in video frames. The tracking includes processing an initial frame of a set of frames, the processing the initial frame using feature extraction to identify locations of features of the at least one object. The tracking further includes using motion estimation to track locations of the features in subsequent frames of the set of frames, including iteratively performing: obtaining a next frame of the set of frames, and applying a motion estimation algorithm as between the next frame and a prior frame of the set of frames to identify updated locations of the features in the next frame, where locations of the features as identified based on the prior frame are used as input to the motion estimation algorithm to identify the updated locations of the features in the next frame based on searching less than an entirety of the next frame.

Abstract: A method includes tracking positions of object(s) in video frames, including: processing an initial frame of a set of frames of the video frames using feature extraction to identify locations of features of the object(s), obtaining a next frame of the set and applying a motion estimation algorithm as between the next frame and a prior frame to identify updated locations of the features in the next frame, where locations of the features as identified based on the prior frame are used as input to the motion estimation algorithm to identify the updated locations of the features in the next frame based one searching less than an entirety of the next frame. The tracking further includes recognizing occurrence of an event, halting the iteratively performing, and repeating, for at least one subsequent set of frames, the processing an initial frame and the using motion estimation.

Abstract: A not crossable element (NCE) is marked using a shape on a map. A map data does not prevent a route from crossing the NCE. A closed area is selected on the map, which includes a polygon bound on one side by a portion of the shape. A set of mapping points (MP) that are included in the closed area is selected. A route is formed by connecting one MP to another MP. A subset of MPs is identified as a set of candidate MPs (CMP). Each CMP lies within a search distance of a not-mapping point (NMP). The CMPs are sorted according to CMP-NMP distances. A subset of CMPs is selected whose paths to the NMP do not intersect with any shape corresponding to any NCE in the closed area. The NMP is linked in the route with a selected CMP from the subset of CMPs.

Abstract: In an approach for locating parking, a computer identifies driving directions to a destination. The computer receives a navigation input from a user to locate parking associated with the destination. The computer calculates one or more navigation paths based on the destination, wherein the one or more navigation paths include one or more street segments that connect identical starting and ending points with at least one different street segment and overall values indicating priority based on one or more weight factors associated with the one or more street segments. The computer selects a first navigation path from the calculated one or more navigation paths utilizing an ordered ranking of the one or more navigation paths. The computer provides driving directions associated with the first navigation path. The computer determines whether the user locates parking while utilizing the first navigation path.

Abstract: In an approach for locating parking, a computer identifies driving directions to a destination. The computer receives a navigation input from a user to locate parking associated with the destination. The computer calculates one or more navigation paths based on the destination, wherein the one or more navigation paths include one or more street segments that connect identical starting and ending points with at least one different street segment and overall values indicating priority based on one or more weight factors associated with the one or more street segments. The computer selects a first navigation path from the calculated one or more navigation paths utilizing an ordered ranking of the one or more navigation paths. The computer provides driving directions associated with the first navigation path. The computer determines whether the user locates parking while utilizing the first navigation path.

Abstract: In an approach for locating parking, a computer identifies driving directions to a destination. The computer receives a navigation input from a user to locate parking associated with the destination. The computer calculates one or more navigation paths based on the destination, wherein the one or more navigation paths include one or more street segments that connect identical starting and ending points with at least one different street segment and overall values indicating priority based on one or more weight factors associated with the one or more street segments. The computer selects a first navigation path from the calculated one or more navigation paths utilizing an ordered ranking of the one or more navigation paths. The computer provides driving directions associated with the first navigation path. The computer determines whether the user locates parking while utilizing the first navigation path.

Abstract: A processor receives a media rating associated with a first media program and metadata associated with the first media program. The processor stores the metadata and the media rating associated with the first media program in a local database. The processor receives a second media program absent a media rating. The processor determines metadata associated with the second media program absent the media rating. The processor searches the local database based on the metadata associated with the second media program absent the parental control rating. The processor matches the metadata associated with the second media program absent the media rating to the metadata of the first media program including the media rating, and the processor applies the media rating of the first media program to the second media program.

Abstract: A processor receives a media rating associated with a first media program and metadata associated with the first media program. The processor stores the metadata and the media rating associated with the first media program in a local database. The processor receives a second media program absent a media rating. The processor determines metadata associated with the second media program absent the media rating. The processor searches the local database based on the metadata associated with the second media program absent the parental control rating. The processor matches the metadata associated with the second media program absent the media rating to the metadata of the first media program including the media rating, and the processor applies the media rating of the first media program to the second media program.

Abstract: A processor receives a media rating associated with a first media program and metadata associated with the first media program. The processor stores the metadata and the media rating associated with the first media program in a local database. The processor receives a second media program absent a media rating. The processor determines metadata associated with the second media program absent the media rating. The processor searches the local database based on the metadata associated with the second media program absent the parental control rating. The processor matches the metadata associated with the second media program absent the media rating to the metadata of the first media program including the media rating, and the processor applies the media rating of the first media program to the second media program.

Abstract: A processor receives a media rating associated with a first media program and metadata associated with the first media program. The processor stores the metadata and the media rating associated with the first media program in a local database. The processor receives a second media program absent a media rating. The processor determines metadata associated with the second media program absent the media rating. The processor searches the local database based on the metadata associated with the second media program absent the parental control rating. The processor matches the metadata associated with the second media program absent the media rating to the metadata of the first media program including the media rating, and the processor applies the media rating of the first media program to the second media program.

Abstract: The invention provides a system and method for retrieving documents from a collection of documents that match a word search query. A word index is generated for each document in which each entry is an enriched-term string built from the stemmed form of the word to be searched and a separator character followed by the original form of the word to be searched. During a retrieving operation, a search query is processed depending the original form or the stemmed form of a word to be searched. Cross-documents tables are addressed to find documents that match the enriched-term string of the word to be searched.