Systems and methods for determining how topics evolve in a messaging system extract at least one N-gram from data content (e.g., caption of messages) in the messaging system and detect anomalous behavior in N-gram frequencies over time. The anomalous behavior is used to select candidate N-grams for a determination of whether a topic of a candidate N-gram is evolving or fading. The candidate N-grams are clustered into cluster groups that are used to train at least one time series forecasting model to predict N-gram frequencies in a future time window. A time series of the N-gram frequency is divided into old and recent partitions and pattern recognition is applied to the predicted N-gram frequencies to identify an evolving or fading topic when the difference between a frequency of each anomaly and an average rolling median for each partition is greater for the most recent partition.

An embodiment includes parsing conversation data to extract a message dataset and a user dataset. The embodiment classifies the message dataset into a category using machine learning processing and identifies the category as a top category based at least in part on an amount of the conversation data associated with the category. The embodiment generates impact data associated with the user dataset based on actions in the conversation data by the user. The embodiment generates role data associated with the user by applying a rule to the conversation data for the user. The embodiment generates key index data associated with the message dataset by identifying interactions with a message represented by the message dataset. The embodiment generates output data arranged according to a specified data format that is compatible with a user interface.

A system to quantify aggregate alignment of segmented text with an evaluator population, with a data processing system comprising memory and one or more processors, can segment a first extended text object into one or more evaluation text objects associated with a population reference, identify one or more text frame objects corresponding to the evaluation text objects, the text frame objects being associated with a second extended text object, generate, based on the text frame objects, one or more context identifier objects corresponding to the evaluation text objects, and generate a condensed text object including one or more of the evaluation text objects, the evaluation text objects being positioned in the condensed text object in response to output of a first machine learning model trained with input including at least one of the first extended text objects, the evaluation text objects, the context identifier objects, and the text frame objects.

In a computer-implemented method for information retrieval and a processing system of a computer-implemented information retrieval system, an input text is received by a Natural Language Processing, NLP, suite, wherein the NLP suite comprises a plurality of models. At least one of the plurality of models is a model trained using selected features. The selected features are determined using a feature selection process. The input text is processed by each one of the plurality of models. An intermediate representation of the input text is generated by each one of the plurality of models. An enhanced representation of the input text is generated by combining a plurality of the generated intermediate representations. Information is retrieved based on the enhanced representation of the input text.

A method for generating a report is provided. The method may include acquiring a key word related to an industry field, and acquiring one or more condition values related to the report to be generated. The method may also include determining a report template having one or more data query sections and one or more conclusion sections based on the industry field and the one or more condition values, and acquiring report data based on the one or more data query sections of the report template. The method may further include determining one or more conclusions based on the report data, and generating the report based the data acquired based on the report data, the one or more conclusions, and the template.

A method of summarizing data files includes implementing, at a server, a storage event for a data file, analyzing the data file and creating a summary of the data file, and storing the summary linked to the data file.

A method and system for detecting, segmenting, and extracting salient regions in documents by using attention tracking sensors is provided. The method includes: receiving an image that corresponds to a document; receiving, from a sensor, a sequence of measurements that correspond to a human reading of the document; determining, based on the sequence of measurements, at least one region of the document as being a salient document region; demarcating the salient document region in an electronically displayable manner; and outputting a file that includes a displayable version of the document with the demarcated document region. The salient document region may include a title, a section header, and/or a table. The sensor may be an eye-tracking sensor that detects a sequence of eye-gaze positions on the document as a function of time.

A method of automatically generating content summaries for topics includes receiving a taxonomy for a concept and a text corpus. The method further includes generating an annotated dataset having term annotations corresponding to the concept from the text corpus based on the taxonomy, parsing the annotated dataset into a custom generated document object having a structured layout, determining features for the term annotations, and extracting snippets from the custom generated document object, where each of the snippets corresponds to a section of the custom generated document object. The method further includes scoring the snippets based on the features such that each of the snippets corresponds to a score, filtering one or more snippets from the snippets when one or more snippet filtering conditions is met, ranking the snippets into an ordered list for the concept based on the score, and providing, to a user computing device, the ordered list.

Systems and methods are provided for a supply knowledge portal. The supply knowledge portal provides a new metric dashboard that delivers real-time information on the status and health of the hospital supply chain. The new dashboard is driven by the transactional data generated from system point of use devices and allows end users to view data at various levels starting at the facility level and moving down to filter for specific areas, devices and, at the lowest level, items.

Methods, systems and programming for presenting a content summary of search results is described herein. In one example, at least one search result may be fetched based on a search query. A determination may be made that a summary has previously been generated for at least some of the at least one search result, and the summary may be retrieved. A search result page including the at least one search result and at least part of the summary may be generated, and the search result page may be sent in response to the search query.