Abstract: A method for obtaining information and status about a monitored system by adaptively analyzing log messages is provided. A log analyzer receives log messages generated by a monitored system. The log analyzer identifies static and variable portions in the received log messages. The log analyzer generates a template based on the identified static and variable portions of the received log messages. The log analyzer computes a metric for the generated template based on a number of log messages that fall within the template. The log analyzer reports a status in the monitored system based on the computed metric.

Abstract: Aspects of the invention include generating a combined raster image from point cloud data and reference data describing an original location of a power line. Selecting a set of candidate pixels from the combined raster image describing an updated location of a power line, wherein the selection is based at least in part on a location of pixels in the combined raster image that describe the original location. Detecting pixels from the set of candidate pixels that describe an updated location of a power line. Modifying the combined raster image to reflect the updated location of the power line.

Abstract: A cloud-enterprise resource management system enables sharing of computing resources belonging to different datacenters by one or more clients of a resource pooling and sharing service. Each datacenter of includes a first partition of computing resources and a second partition of computing resources. The first partition is designated as reserved for use by an enterprise operating the datacenter. The second partition is designated as available for use by one or more clients of the resource pooling and sharing service. A workload manager in each datacenter predicts workload and transfers (i) a first computing resource from the first partition to the second partition wherein when the predicted workload is below a first threshold and (ii) a second computing resource from the second partition to the first partition when the predicted workload is above a second threshold.

Abstract: Provided are a method, system, and computer program product for representing text, in which a text is received and analyzed by utilizing a pre-trained embedding model and a feature vector model, wherein selected words in the text have corresponding weights. Operations whose parameters include weights of a feature vector and an embedding are performed to generate a weighted embedding data structure. A summation is performed of all corresponding columns of a plurality of rows of the weighted embedding data structure to generate a data structure that represents the text. The data structure that represents the text is utilized to generate at least one of a classification metadata for the text and a summarization of the text.

Abstract: Embodiments for implementing intelligent customer journey prediction and customer segmentation of a processor in a computing environment. A response outcome of a customer journey for a user may be predicted according to an assigned score based on one or more discriminatory sequence patterns identified between one or more groups of customers using one or more machine learning operations.

Abstract: Aspects of the invention include receiving a point cloud data set describing a target area. Receiving a first parameter describing a power line segment at an original location within the target area. Using the processor to extract from the point cloud data set a power line segment at an updated location distinct from the original location, wherein analysis of each candidate data point of the point cloud data set is constrained by the first parameter, and wherein the first parameter causes the power line segment at the updated location to be parallel with the power line segment at the original location. Generating a vector describing the updated location of the power line segment with respect to geospatial coordinates of the target area.

Abstract: Aspects of the invention include methods of performing beam management in a base station of a cellular network. A method includes obtaining, at the base station, information indicating whether one or more terminals of the cellular network have data to transmit, and determining, using the base station, during a sweep by the base station if an upcoming terminal has data to transmit based on the information. The sweep by the base station is a sequential movement of the beam over a coverage area. The method also includes foregoing, by the base station, any communication with the upcoming terminal during the sweep based on the information indicating that the upcoming terminal has no data to transmit, and communicating, using the base station, with the upcoming terminal during the sweep based on the information indicating that the upcoming terminal has data to transmit.

Abstract: Aspects of the invention include receiving, by a processor, airspace data associated with a predefined airspace, obtaining roadway data associated with the predefined airspace, determining a set of air travel channels within the predefined airspace based on the roadway data, defining a set of travel lanes within the set of air travel channels, wherein each travel lane in the set of travel lanes comprises an altitude range, receiving unmanned aircraft (UA) data associated with a set of UAs within the predefined airspace, wherein the UA data comprises one or more flight paths for each UA in the set of UAs, and assigning each UA in the set of UAs to a travel lane in the set of travel lanes based on the one or more flight paths.

Abstract: A method and system for extracting information from a drawing. The method includes classifying nodes in the drawing, extracting attributes from the nodes, determining whether there are errors in the node attributes, and removing the nodes from the drawing. The method also includes identifying edges in the drawing, extracting attributes from the edges, and determining whether there are errors in the edge attributes. The system includes at least one processing component, at least one memory component, an identification component, an extraction component, and a correction component. The identification component is configured to classify nodes in the drawing, remove the nodes from the drawing, and identify edges in the drawing. The extraction component is configured to extract attributes from the nodes and edges. The correction component is configured to determine whether there are errors in the extracted attributes.

Abstract: A computer-implemented method for delivering network connectivity includes receiving, by an edge server, a set of communication packets from a communication device. The method further includes storing, by the edge server, the set of communication packets as part of outbound data. The method further includes determining, by the edge server, that a mobile access point is within a communicable range of the edge server. The mobile access point travels back and forth between the edge server and a base station. The method further includes transmitting, by the edge server, the outbound data to the mobile access point that is within the communicable range.

Abstract: A spatial-temporal storage method, system, and non-transitory computer readable medium include dynamically managing a plurality of region servers for querying spatiotemporal data in noSQL databases.

Abstract: Methods and systems for detecting events. A satellite image is obtained and the satellite image is processed using a first convolutional neural network (CNN) to produce a satellite vector that identifies at least one fire. A mobile sensor is automatically directed to a mobile location based on the satellite vector.

Abstract: Embodiments of the invention include method, systems and computer program products for document vectorization. Aspects include receiving, by a processor, a plurality of documents each having a plurality of word. The processor utilizing a vector embeddings engine generates a vector to represent each of the plurality of words in the plurality of documents. An image representation for each document in the plurality of documents is created and a word probability for each of the plurality of words in the plurality of documents is generated. A position for each word probability is determined in the image based on the vector associated with each word and a compression operation on the images is performed to produce a compact representation for the plurality of documents.

Abstract: An input dataset for training a new machine learning model is received by a processor. For each of a plurality of trained machine learning models, a hash function and a sketch of a training dataset used to train the machine learning model is retrieved. A sketch of the input dataset is computed based on the hash function and the input dataset, along with a distance between the sketch of the training dataset and the sketch of the input dataset. The computed distances of the trained machine learning models are ranked from smallest to largest, and a seed machine learning model for the input dataset is selected from the trained machine learning models based at least in part on the ranking. A training process of the new machine learning model using the selected seed machine learning model and the input dataset is initiated.

Abstract: Aspects of the invention include methods of performing beam management in a base station of a cellular network. A method includes obtaining, at the base station, information indicating whether one or more terminals of the cellular network have data to transmit, and determining, using the base station, during a sweep by the base station if an upcoming terminal has data to transmit based on the information. The sweep by the base station is a sequential movement of the beam over a coverage area. The method also includes foregoing, by the base station, any communication with the upcoming terminal during the sweep based on the information indicating that the upcoming terminal has no data to transmit, and communicating, using the base station, with the upcoming terminal during the sweep based on the information indicating that the upcoming terminal has data to transmit.

Abstract: A computer-implemented method for delivering network connectivity includes receiving, by an edge server, a set of communication packets from a communication device. The method further includes storing, by the edge server, the set of communication packets as part of outbound data. The method further includes determining, by the edge server, that a mobile access point is within a communicable range of the edge server. The mobile access point travels back and forth between the edge server and a base station. The method further includes transmitting, by the edge server, the outbound data to the mobile access point that is within the communicable range.

Abstract: A computer-implemented method for generating and deploying a reinforced learning model to train a chatbot. The method includes selecting a plurality of conversations, wherein each conversation includes an agent and a user. The method includes identifying, in each of the conversations, a set of turns and on or more topics. The method further includes associating one or more topics to each turn of the set of turns. The method includes, generating a conversation flow for each conversation, wherein the conversation flow identifies a sequence of the topics. The method includes applying an outcome score to each conversation. The method includes creating a reinforced learning (RL) model, wherein the RL model includes a Markov is based on the conversation flow of each conversation and the outcome score of each conversation. The method includes deploying the RL model, wherein the deploying includes sending the RL model to a chatbot.

Abstract: Methods and systems for detecting events. A satellite image is obtained and the satellite image is processed using a first convolutional neural network (CNN) to produce a satellite vector that identifies at least one fire. A mobile sensor is automatically directed to a mobile location based on the satellite vector.

Abstract: A method and system for extracting information from a drawing. The method includes classifying nodes in the drawing, extracting attributes from the nodes, determining whether there are errors in the node attributes, and removing the nodes from the drawing. The method also includes identifying edges in the drawing, extracting attributes from the edges, and determining whether there are errors in the edge attributes. The system includes at least one processing component, at least one memory component, an identification component, an extraction component, and a correction component. The identification component is configured to classify nodes in the drawing, remove the nodes from the drawing, and identify edges in the drawing. The extraction component is configured to extract attributes from the nodes and edges. The correction component is configured to determine whether there are errors in the extracted attributes.

Abstract: A parse tree corresponding to a portion of narrative text is constructed. The parse tree includes a data structure representing a syntactic structure of the portion of narrative text as a set of tokens according to a grammar. Using a token in the parse tree as a focus word, a context window comprising a set of words within a specified distance from the focus word is generated, the distance determined according to a number of links of the parse tree separating the focus word and a context word in the set of words. A weight is generated for the focus word and the context word. Using the weight, a first vector representation of a first word is generated, the first word being within a second portion of narrative text.