Data analytics systems and methods are disclosed herein. A parser can parse reference data from various data sources to store in a data structure. An uploader can receive study data designated by a researcher and store the study data in the data structure. A matcher can compare analyte nameset data in the study data with analyte nameset data from the reference data to generate one or more links each correlating an instance of an analyte in the study data with an instance of that analyte in the reference data. Library overlays each include one or more modules to access reference data to generate organized associations of reference data. A calculation engine can receive a selection of one or more library overlay(s) and manipulate the reference data and study data according to the organized associations of the selected library overlay(s) to generate configured data stored in a collection of data caches for presentation to a researcher via a user interface.

A system and method including receiving sets of sensor data associated with sensors configured to monitor one or more systems. Sensor fingerprints are generated for each set of sensor data based on the sensor data. At least one proximity value is computed for each sensor by comparing the fingerprint of that sensor with another fingerprint. Clusters of similar sensors are identified based at least upon the proximity values of the sensors.

A method, a computer program product, and a computer system manage meeting divergence for a meeting involving a plurality of participants to discuss a plurality of core intents. The method includes receiving a first contribution from a first one of the participants during the meeting. The method includes determining a first one of the core intents that the first contribution is associated. The method includes determining a linkage of the first contribution to at least one second, previous contribution provided during the meeting. The method includes generating a graphical representation of a progress of the meeting, the graphical representation including a first visual indicator corresponding to the first contribution and at least one second visual indicator respectively corresponding to the at least one second contribution. The first visual indicator is positioned with respect to the at least one second visual indicator to represent the linkage.

A method and system for recommending articles including: receiving a customer request from the customer during the session; generating case data for a case, by an article recommender app; configuring a training set based on the subject and description data of the customer request; identifying, by an artificial intelligence (AI) app, a first pool of articles from a knowledge database; identifying by at least one query, a second pool of articles from a case article database to into a merged pool of articles; assigning, by the AI app, an implicit label to one of the first pool and the second pool of the articles; applying a model derived by the AI app based on customer behavior and a set of features related to the case to classify each article of the merged pool of articles based at least in part on the predicted relevance of the article.

A method and system for recommending articles including: receiving a customer request from the customer during the session; generating case data for a case, by an article recommender app; configuring a training set based on the subject and description data of the customer request; identifying, by an artificial intelligence (AI) app, a first pool of articles from a knowledge database; identifying by at least one query, a second pool of articles from a case article database to into a merged pool of articles; assigning, by the AI app, an implicit label to one of the first pool and the second pool of the articles; applying a model derived by the AI app based on customer behavior and a set of features related to the case to classify each article of the merged pool of articles based at least in part on the predicted relevance of the article.

One embodiment of the invention provides a method for speaker identity and content de-identification under privacy guarantees. The method comprises receiving input indicative of privacy protection levels to enforce, extracting features from a speech recorded in a voice recording, recognizing and extracting textual content from the speech, parsing the textual content to recognize privacy-sensitive personal information about an individual, generating de-identified textual content by anonymizing the personal information to an extent that satisfies the privacy protection levels and conceals the individual's identity, and mapping the de-identified textual content to a speaker who delivered the speech. The method further comprises generating a synthetic speaker identity based on other features that are dissimilar from the features to an extent that satisfies the privacy protection levels, and synthesizing a new speech waveform based on the synthetic speaker identity to deliver the de-identified textual content. The new speech waveform conceals the speaker's identity.

The present teaching relates to providing a query suggestion. In one example, a request is received for query suggestions with respect to a query prefix input by a user. A plurality of query suggestions is determined based on the query prefix and a preceding query input by the user. A degree of popularity of the preceding query is determined. One or more query suggestions are selected from the plurality of query suggestions based on the degree of popularity of the preceding query. The one or more query suggestions are provided as a response to the request.

The present teaching relates to providing a query suggestion. In one example, a request is received for query suggestions with respect to a query prefix input by a user. A plurality of query suggestions is determined based on the query prefix and a preceding query input by the user. A degree of popularity of the preceding query is determined. One or more query suggestions are selected from the plurality of query suggestions based on the degree of popularity of the preceding query. The one or more query suggestions are provided as a response to the request.

Some embodiments may perform operations of a process that includes obtaining a natural language text document and use a machine learning model to generate a set of attributes based on a set of machine-learning-model-generated classifications in the document. The process may include performing hierarchical data extraction operations to populate the attributes, where different machine learning models may be used in sequence. The process may include using a pre-trained Bidirectional Encoder Representations from Transformers (BERT) model augmented with a pooling operation to determine a BERT output via a multi-channel transformer model to generate vectors on a per-sentence level or other per-text-section level. The process may include using a finer-grain model to extract quantitative or categorical values of interest, where the context of the per-sentence level may be retained for the finer-grain model.

Techniques are disclosed for content storage in a way that facilitates consistent and concurrent read/write processing of stored documents. An example methodology implementing the techniques includes segmenting the contents of a document into a plurality of content segments and storing the plurality of content segments within a data structure, the data structure including storage blocks having storage portions and buffer portions. The storage of the plurality of content segments includes storage of content segments within a storage portions of the storage blocks of the data structure. The method also includes receiving at least one change to the content and utilizing a buffer portion of at least one storage block to store the at least one change to the content.