Clustering structured log data by key-values includes receiving, via a user interface, a request to apply an operator to cluster a set of raw log messages according to values for a set of keys associated with the request. At least a portion of each raw log message comprises structured machine data including a set of key-value pairs. It further includes receiving a raw log message in the set of raw log messages. It further includes determining whether to include the raw log message in a cluster based at least in part on an evaluation of values in the structured machine data of the raw log message for the set of keys associated with the request. The cluster is included in a plurality of clusters. Each cluster in the plurality is associated with a different combination of values for the set of keys associated with the request. It further includes providing, via the user interface, information associated with the cluster.

Method, system, and programs for determining a keyword from user agent strings are disclosed. In one example, a plurality of user agent strings is received. The plurality of user agent strings is grouped into one or more clusters. The one or more clusters comprise a first cluster that includes two or more user agent strings. The two or more user agent strings in the first cluster are compared. Based on the comparing, a keyword is determined from the first cluster. The keyword represents a type of user agent information.

The present disclosure relates to extracting key concepts from digital content items and determining associations between the key concepts and candidate terms for use in generating and presenting a correlation graph object based on the determined associations. For example, systems described herein involve determining frequency of co-occurrence between various key concepts and applying a classification model (e.g., a zero-shot classification model) to the key concepts and candidate terms to determine associations between the key concepts and candidate terms for a given domain of interest. The systems further involve generating a graph object and processing graph queries in a way that enables fast and efficient presentation of slices of the graph object that provide a visual depiction of key concepts and edges representing associations between pairs of the key concepts.

The present disclosure provides a data updating method and apparatus, electronic device, and computer readable storage medium. The method includes: acquiring a search sentence; determining a target query sentence corresponding to the search sentence according to a sentence type corresponding to the search sentence; determining a target search content according to the search sentence, and sending the target search content to a service side, in the case that a query result corresponding to the target query sentence is not found in a knowledge base; acquiring a target query result edited by the service side according to the target search content; and updating the knowledge base according to the target query result.

Systems and methods are provided for dynamically grouping data analysis content derived from a plurality of sensors. In one embodiment, a plurality of sensors can be disposed on a plurality of machine trains or one or more machines within the plurality of machine trains configured in an industrial environment. A communication circuit can be operatively coupled to the plurality of sensors and configured to communicate data measured by the plurality of sensors, and a dynamic graphical user interface (GUI) can be provided on a touchscreen display and can be configured to dynamically generate one or more visualizations of the measured data. A processor can be configured to receive the measured data via the communication circuit, to generate a plurality of measurements based on the measured data, and to operatively control the dynamic GUI in response to a grouping mode selection.

Methods, systems, and devices for analyzing communication messages (e.g., emails or activities) to determine relationship strength using a distributed graph are described. In some systems, a user may be associated with a specific tenant. A database server of the system may receive communication messages associated with the user and a target user. The server may perform a natural language processing (NLP) analysis on the communication messages to extract metadata, and may generate or update a distributed graph indicating connections between users based on the extracted metadata. Using the connections of the graph, the server may calculate a closeness score between the user and the target user. Additionally, the server may calculate closeness scores between the target and other users associated with the tenant, and may determine the users with the greatest closeness scores. The server may send a suggestion for the determined users to initiate communication with the target.

Systems and processes for operating a digital assistant are provided. In accordance with one or more examples, a method includes, at a user device with one or more processors and memory, receiving unstructured natural language information from at least one user. The method also includes, in response to receiving the unstructured natural language information, determining whether event information is present in the unstructured natural language information. The method further includes, in accordance with a determination that event information is present within the unstructured natural language information, determining whether an agreement on an event is present in the unstructured natural language information. The method further includes, in accordance with a determination that an agreement on an event is present, determining an event type of the event and providing an event description based on the event type.

Various methods and systems of statistical data processing and natural-language-processing are disclosed. According to one embodiment, an intelligent, automated KPI-discovery method uses existing machine-learning algorithms and Natural Language Processing (NLP) for extraction and construction of KPIs.

Methods and systems are disclosed that analyze patent-related documents having at least one property type. In one implementation, a method involves displaying, in a first graphical element, identifiers of the patent-related documents. The method also involves analyzing the patent-related documents to determine at least one property value for the property type. The property value includes a string of one or more words describing subject matter associated with the patent-related documents and occurring in a subset of the patent-related documents. The method also displays a second graphical element associated with the property type. The second graphical element includes the property value. The method receives, at the second graphical element, a user selection of the property value. The method displays, in the first graphical element, identifiers of the subset of the patent-related documents in which the property value occurs.

Systems and methods provide for classification and ranking of features for a hierarchical dataset. A hierarchical schema of features from the dataset is accessed. A hierarchical rank is assigned to each feature based on its schema level in the hierarchical schema. Additionally, a semantic rank is assigned to each feature using a semantic model having ranked semantic contexts. The semantic rank of a feature is assigned by identifying a semantic context of the feature and assigning the rank of the semantic context as the semantic rank of the feature. A rank is computed for each feature as a function of its hierarchical rank and semantic rank.