Abstract: A messaging system performs trend analysis on content produced by users of the messaging system. The messaging system is configured to extract modifications from content items received from client devices associated with users where the content items are modified using the modifications that comprises a text caption or a media overlay. The messaging system is further configured to determine one or more words from the content items and the extracted modifications and determine a frequency of the one or more words in the content items and the extracted modifications. The messaging system is further configured to determine whether the one or more words is a trend based on the frequency and an aggregate frequency. The messaging system is further configured to in response to the one or more words being determined as the trend, generating trend content associated with the one or more words, the trend content being a text, an image, or an augmentation content.

Abstract: A messaging system performs engagement analysis based on labels associated with content items produced by users of the messaging system. The messaging system is configured to process content items comprising images to identify elements in the images and determine labels for the images based on conditions indicating when to associate a label of the labels with an image of the images based on the elements in the image. The messaging system is further configured to associate the label with the content item, in response to determining to associate the label with the image, associating the label with the content item. The messaging system is further configured to determine engagement scores for the label based on interactions of users with the content items associated with label and adjust the engagement scores to determine trends in the labels to generate adjusted engagement scores.

Abstract: A messaging system performs engagement analysis based on labels associated with content items produced by users of the messaging system. The messaging system is configured to process content items comprising images to identify elements in the images and determine labels for the images based on conditions indicating when to associate a label of the labels with an image of the images based on the elements in the image. The messaging system is further configured to associate the label with the content item, in response to determining to associate the label with the image, associating the label with the content item. The messaging system is further configured to determine engagement scores for the label based on interactions of users with the content items associated with label and adjust the engagement scores to determine trends in the labels to generate adjusted engagement scores.

Abstract: Systems, devices, media, and methods are presented for identifying emerging viewing patterns for visual media such as still images and videos. Emerging viewing patterns are identified by identifying visual tags for visual media viewed by users, selecting a subset of the tags by applying a taxonomy-based filter, generating pattern candidates from the subset, evaluating consumption metrics for each of the generated patterns, and ranking the generated pattern candidates responsive to the consumption metrics to identify emerging viewing patterns for the users.

Abstract: Facilitating detection of anomalies of a target entity is provided herein. A system can comprise a processor and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations. The operations can comprise training a model on a first set of variables that are constrained by a second set of variables. The second set of variables can characterize elements of a defined entity. The first set of variables can define a normality of the defined entity. The operations also can comprise employing the model to identify expected parameters and unexpected parameters associated with the defined entity to at least a defined level of confidence.

Abstract: Systems, devices, media, and methods are presented for identifying emerging viewing patterns for visual media such as still images and videos. Emerging viewing patterns are identified by identifying visual tags for visual media viewed by users, selecting a subset of the tags by applying a taxonomy-based filter, generating pattern candidates from the subset, evaluating consumption metrics for each of the generated patterns, and ranking the generated pattern candidates responsive to the consumption metrics to identify emerging viewing patterns for the users.

Abstract: A messaging system performs trend analysis on content produced by users of the messaging system. The messaging system is configured to extract modifications from content items received from client devices associated with users where the content items are modified using the modifications that comprises a text caption or a media overlay. The messaging system is further configured to determine one or more words from the content items and the extracted modifications and determine a frequency of the one or more words in the content items and the extracted modifications. The messaging system is further configured to determine whether the one or more words is a trend based on the frequency and an aggregate frequency. The messaging system is further configured to in response to the one or more words being determined as the trend, generating trend content associated with the one or more words, the trend content being a text, an image, or an augmentation content.

Abstract: 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.

Abstract: A messaging system performs trend analysis on content produced by users of the messaging system. The messaging system is configured to extract modifications from content items received from client devices associated with users where the content items are modified using the modifications that comprises a text caption or a media overlay. The messaging system is further configured to determine one or more words from the content items and the extracted modifications and determine a frequency of the one or more words in the content items and the extracted modifications. The messaging system is further configured to determine whether the one or more words is a trend based on the frequency and an aggregate frequency. The messaging system is further configured to in response to the one or more words being determined as the trend, generating trend content associated with the one or more words, the trend content being a text, an image, or an augmentation content.

Abstract: Systems, devices, media, and methods are presented for identifying emerging viewing patterns for visual media such as still images and videos. Emerging viewing patterns are identified by identifying visual tags for visual media viewed by users, selecting a subset of the tags by applying a taxonomy-based filter, generating pattern candidates from the subset, evaluating consumption metrics for each of the generated patterns, and ranking the generated pattern candidates responsive to the consumption metrics to identify emerging viewing patterns for the users.

Abstract: Facilitating temporal data management for anomalous state detection in data centers is provided herein. A system can comprise a processor and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations. The operations can comprise performing a process of extraction, transformation, and loading of data from log files into a telemetry data store. The data can be loaded into the telemetry data store as telemetry data. The operations also can comprise dividing the telemetry data into first telemetry data and second telemetry data. The first telemetry data can comprise telemetry data that does not satisfy a defined quality level. The second telemetry data can comprise telemetry data that satisfies the defined quality level. Further, the operations can comprise removing the first telemetry data from the telemetry data store and outputting the second telemetry data based on a request for the second telemetry data.

Abstract: Facilitating detection of anomalies of a target entity is provided herein. A system can comprise a processor and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations. The operations can comprise training a model on a first set of variables that are constrained by a second set of variables. The second set of variables can characterize elements of a defined entity. The first set of variables can define a normality of the defined entity. The operations also can comprise employing the model to identify expected parameters and unexpected parameters associated with the defined entity to at least a defined level of confidence.

Abstract: Systems, devices, media, and methods are presented for identifying emerging viewing patterns for visual media such as still images and videos. Emerging viewing patterns are identified by identifying visual tags for visual media viewed by users, selecting a subset of the tags by applying a taxonomy-based filter, generating pattern candidates from the subset, evaluating consumption metrics for each of the generated patterns, and ranking the generated pattern candidates responsive to the consumption metrics to identify emerging viewing patterns for the users.

Abstract: A messaging system performs engagement analysis based on labels associated with content items produced by users of the messaging system. The messaging system is configured to process content items comprising images to identify elements in the images and determine labels for the images based on conditions indicating when to associate a label of the labels with an image of the images based on the elements in the image. The messaging system is further configured to associate the label with the content item, in response to determining to associate the label with the image, associating the label with the content item. The messaging system is further configured to determine engagement scores for the label based on interactions of users with the content items associated with label and adjust the engagement scores to determine trends in the labels to generate adjusted engagement scores.

Abstract: Systems, devices, media, and methods are presented for identifying emerging viewing patterns for visual media such as still images and videos. Emerging viewing patterns are identified by identifying visual tags for visual media viewed by users, selecting a subset of the tags by applying a taxonomy-based filter, generating pattern candidates from the subset, evaluating consumption metrics for each of the generated patterns, and ranking the generated pattern candidates responsive to the consumption metrics to identify emerging viewing patterns for the users.

Abstract: Facilitating detection of anomalies of a target entity is provided herein. A system can comprise a processor and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations. The operations can comprise training a model on a first set of variables that are constrained by a second set of variables. The second set of variables can characterize elements of a defined entity. The first set of variables can define a normality of the defined entity. The operations also can comprise employing the model to identify expected parameters and unexpected parameters associated with the defined entity to at least a defined level of confidence.

Abstract: A method for managing storage devices includes obtaining, by a storage device event manager, a set of storage device telemetry snapshots is associated with a set of storage devices, generating a telemetry summary correlation matrix using the set of storage device telemetry snapshots, performing, using the telemetry summary correlation matrix, a classification of each storage device in the set of storage devices to obtain a set of classification tags using a first portion of a set of features, obtaining a set of normality states for the set of storage devices using the set of classification tags and a second portion of the set of features, updating an event anomaly policy based on the set of normality states, and performing a remediation action on a storage device in the set of storage devices based on the event anomaly policy.

Abstract: Facilitating temporal data management for anomalous state detection in data centers is provided herein. A system can comprise a processor and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations. The operations can comprise performing a process of extraction, transformation, and loading of data from log files into a telemetry data store. The data can be loaded into the telemetry data store as telemetry data. The operations also can comprise dividing the telemetry data into first telemetry data and second telemetry data. The first telemetry data can comprise telemetry data that does not satisfy a defined quality level. The second telemetry data can comprise telemetry data that satisfies the defined quality level. Further, the operations can comprise removing the first telemetry data from the telemetry data store and outputting the second telemetry data based on a request for the second telemetry data.

Abstract: A messaging system performs trend analysis on content produced by users of the messaging system. The messaging system is configured to extract modifications from content items received from client devices associated with users where the content items are modified using the modifications that comprises a text caption or a media overlay. The messaging system is further configured to determine one or more words from the content items and the extracted modifications and determine a frequency of the one or more words in the content items and the extracted modifications. The messaging system is further configured to determine whether the one or more words is a trend based on the frequency and an aggregate frequency. The messaging system is further configured to in response to the one or more words being determined as the trend, generating trend content associated with the one or more words, the trend content being a text, an image, or an augmentation content.

Abstract: Techniques are provided for data discovery and data integration in a data lake. One method comprises obtaining data files from a data lake, wherein each data file comprises multiple records having multiple fields; selecting multiple candidate fields from a data file based on a record type; determining a relevance score for each candidate field from the data file based on multiple features extracted from the data file; and clustering the scored candidate fields into clusters of similar domains using a hashing algorithm, wherein a given cluster comprises candidate fields, wherein multiple data files can be integrated based on a domain of the candidate fields in the given cluster. The relevance score for each candidate field is based on multiple features comprising, for example, features that take into account a morphological or semantic similarity between file name, file metadata and/or file records and features that consider statistics of candidate fields in a data file.