Abstract: Systems, methods, and machine-readable media for predicting interruptions to the use of spare cloud resources and rebalancing based on those predictions are disclosed. A computing platform collects data for customers over time. The computing platform runs a machine learning algorithm on the historical data to generate a prediction classifier. The prediction classifier relates to a time window for prediction into the future, on the order of minutes or hours. The prediction classifier is run on monitored data from ongoing activity with a cloud provider to generate a risk score. Each risk score may identify an amount of risk that a spare cloud resource related to new resource metrics data will be interrupted within the future time frame corresponding to that prediction classifier. If predicted to be interrupted, the customer may be assisted in rebalancing to other resources. As a result, interruptions can be predicted hours into the future.

Abstract: A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a correlation component that, based on a first context defining a first spare resource instance to be utilized in a networked system, identifies a second spare resource instance, and an evaluation component that generates an availability score defining prediction of availability of the first spare resource instance based on a second context defining the second spare resource instance, wherein the evaluation component further deploys the first spare resource instance, based on the availability score, in the networked system.

Abstract: Systems and methods for identifying anomalous activities in a cloud computing environment are provided. According to one embodiment, a customer's infrastructure may be fortified by leveraging deep learning technology (e.g., an encoder-decoder machine-learning (ML) model) to predict events in the cloud environment. During a training phase, the ML model may be trained to make a prediction regarding a next event based on a predetermined or configurable length of a sequence of contextual events. For example, historical events (e.g., cloud application programming interface (API) events logged to a cloud activity trace) observed within the customer's cloud infrastructure over the course of a particular date range may be split into appropriate event/context pairs and fed to the ML model. Subsequently, during a run-time anomaly detection phase, the ML model may be used to predict a next event based on a sequence of immediately preceding events to facilitate identification of anomalous activity.

Abstract: Various methods and systems for processing web crawling queries using a web crawling prioritization model based on classification operation performance. A classification operation for organizing products in a product listing platform is accessed. A web crawling engine is accessed for the classification operation. The web crawling engine operates based on a web crawling query prioritization model that supports determining web crawling priority scores that indicate a predicted performance improvement for classification operations executed with known data and web crawled data to be retrieved from executing a web crawling query operation. Using the web crawling prioritization model, a web crawling priority score is determined for a web crawling query for the corresponding classification operation. The classification operation is associated with a product in a product listing platform and known data for the product.

Abstract: Systems, methods, and machine-readable media for predicting interruptions to the use of spare cloud resources and rebalancing based on those predictions are disclosed. A computing platform collects data for customers over time. The computing platform runs a machine learning algorithm on the historical data to generate a prediction classifier. The prediction classifier relates to a time window for prediction into the future, on the order of minutes or hours. The prediction classifier is run on monitored data from ongoing activity with a cloud provider to generate a risk score. Each risk score may identify an amount of risk that a spare cloud resource related to new resource metrics data will be interrupted within the future time frame corresponding to that prediction classifier. If predicted to be interrupted, the customer may be assisted in rebalancing to other resources. As a result, interruptions can be predicted hours into the future.

Abstract: Various methods and systems for processing web crawling queries using a web crawling prioritization model based on classification operation performance. A classification operation for organizing products in a product listing platform is accessed. A web crawling engine is accessed for the classification operation. The web crawling engine operates based on a web crawling query prioritization model that supports determining web crawling priority scores that indicate a predicted performance improvement for classification operations executed with known data and web crawled data to be retrieved from executing a web crawling query operation. Using the web crawling prioritization model, a web crawling priority score is determined for a web crawling query for the corresponding classification operation. The classification operation is associated with a product in a product listing platform and known data for the product.

Abstract: Various methods and systems for processing web crawling queries using a web crawling prioritization model based on classification operation performance. A classification operation for organizing products in a product listing platform is accessed. A web crawling engine is accessed for the classification operation. The web crawling engine operates based on a web crawling query prioritization model that supports determining web crawling priority scores that indicate a predicted performance improvement for classification operations executed with known data and web crawled data to be retrieved from executing a web crawling query operation. Using the web crawling prioritization model, a web crawling priority score is determined for a web crawling query for the corresponding classification operation. The classification operation is associated with a product in a product listing platform and known data for the product.

Abstract: Various methods and systems for processing web crawling queries using a web crawling prioritization model based on classification operation performance. A classification operation for organizing products in a product listing platform is accessed. A web crawling engine is accessed for the classification operation. The web crawling engine operates based on a web crawling query prioritization model that supports determining web crawling priority scores that indicate a predicted performance improvement for classification operations executed with known data and web crawled data to be retrieved from executing a web crawling query operation. Using the web crawling prioritization model, a web crawling priority score is determined for a web crawling query for the corresponding classification operation. The classification operation is associated with a product in a product listing platform and known data for the product.

Abstract: A handcraft construction element comprising a substantially square central engagement portion defining a diagonal slit therethrough and two oppositely disposed triangular integral flaps extending on opposite sides of said engagement portion and separated therefrom by integral hinges, wherein each of said flaps defines an extended tongue adapted to engage said diagonal slit of another such element; and a sheet having a plurality of handcraft construction elements pre-cut for punching out.

Abstract: An apparatus and method for attaching novelty articles, such as small precious stones, to a plant for display. A dicotyledonous seed is secured in a cage to which is attached the novelty article, and the seed, cage, and novelty article are buried in a planting medium, such that when the plant grows from the seed, the novelty article is secured thereto.