A technique includes, for each storage device of a plurality of storage devices, applying, by a processor, fuzzy logic to assign the plurality of storage devices to respective storage classes based on the weights that are assigned to the plurality of storage devices. The technique includes assigning, by the processor, weights to attributes of a data source. In response to an operation to backup data of the data source, mapping, by the processor, the data source to a given storage device based on the weights that are assigned to the attributes of the data source and the storage class that is associated with the given storage device.

A software robot is designed to carry out an activity (e.g., a mouse click, a text input, etc.) on a target element (e.g., a button, an input field, etc.) of a user interface. The robot is configured to automatically identify the target element at runtime according to a set of attributes of the target element specified in the source-code of the user interface. The robot's code specification includes an indicator of a selected fuzzy attribute and a numerical similarity threshold indicative of an acceptable degree of mismatch between design-time and runtime values of the respective fuzzy attribute. The robot is configured to identify the target element from a set of candidates which are sufficiently similar to it according to the specified degree of mismatch.

This disclosure relates generally to a method and system for muting of classified information from an audio using a fuzzy approach. The method comprises converting the received audio signal into text using a speech recognition engine to identify a plurality of classified words from the text to obtain a first set of parameters. Further, a plurality of subwords associated with each classified word are identified to obtain a second set of parameters associated with each subword of corresponding classified word. A relative score is computed for each subword associated with the classified word based on a plurality of similar pairs for the corresponding classified word. A fuzzy muting function is generated using the first set of parameters, the second set of parameters and the relative score associated with each subword. The plurality of subwords associated with each classified word is muted in accordance with the generated fuzzy muting function.

A software robot is designed to carry out an activity (e.g., a mouse click, a text input, etc.) on a target element (e.g., a button, an input field, etc.) of a user interface. The robot is configured to automatically identify the target element at runtime according to a set of attributes of the target element specified in the source-code of the user interface. The robot's code specification includes an indicator of a selected fuzzy attribute and a numerical similarity threshold indicative of an acceptable degree of mismatch between design-time and runtime values of the respective fuzzy attribute. The robot is configured to identify the target element from a set of candidates which are sufficiently similar to it according to the specified degree of mismatch.

A method is provided, including: storing comments generated in response to a content item served over a network; analyzing the comments to determine features associated with each of the comments; using a scoring model to score each comment based on the comment's corresponding features; receiving a request to serve a subset of the comments; responsive to the request, selecting a ranking of the comments that is one permutation from possible rankings of the comments, wherein selecting the ranking is in accordance with a probability distribution of the possible rankings that is based on the scores of the comments; serving comments identified by the selected ranking over the network to a client device; determining a dwell time on the served comments; applying the dwell time to update the scoring model.

According to an embodiment, 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 an extrapolation component that extrapolates a system parameter of a parameter set to determine a starting parameter value of a variational circuit. The computer executable components can further comprise a variational component that determines a system parameter value of the parameter set based on the starting parameter value.

A technique includes, for each storage device of a plurality of storage devices, applying, by a processor, fuzzy logic to assign the plurality of storage devices to respective storage classes based on the weights that are assigned to the plurality of storage devices. The technique includes assigning, by the processor, weights to attributes of a data source. In response to an operation to backup data of the data source, mapping, by the processor, the data source to a given storage device based on the weights that are assigned to the attributes of the data source and the storage class that is associated with the given storage device.

This disclosure relates generally to a method and system for muting of classified information from an audio using a fuzzy approach. The method comprises converting the received audio signal into text using a speech recognition engine to identify a plurality of classified words from the text to obtain a first set of parameters. Further, a plurality of subwords associated with each classified word are identified to obtain a second set of parameters associated with each subword of corresponding classified word. A relative score is computed for each subword associated with the classified word based on a plurality of similar pairs for the corresponding classified word. A fuzzy muting function is generated using the first set of parameters, the second set of parameters and the relative score associated with each subword. The plurality of subwords associated with each classified word is muted in accordance with the generated fuzzy muting function.

A system for determining code ancestry. The system includes: a memory; and a processor communicatively coupled to the memory. The processor is configured to perform a method comprising: receiving a source code file; parsing a plurality of functions out of the source code file; generating fuzzy fingerprints from the plurality of functions; and storing the fuzzy fingerprints in a graph database.

A system and method of responding to fuzzing including receiving a fuzzing input while in fuzzed mode, performing a perceptual hashing function using the fuzzing input to generate a perceptual hash value, selecting an action from a list of actions using the perceptual hash value, and performing the selected action in response to the fuzzing input. Parameters may be generated using the perceptual hash value for actions that use parameters. Instead of normal hashing, perceptual hashing generates the same hash value for substantially similar fuzzing inputs so that corresponding fuzzing response actions appear to be random but instead are intentional. Hardware or software version numbers may be combined with a shared secret key and hashed using a non-perceptual hashing function to further impede comparison analysis by a fuzzer. Some embodiments combine perceptual hashing with non-perceptual hashing, such as cryptographic hashing or the like.