Abstract: A system for monitoring a plurality of storage systems includes an interface specifying a set of methods for using at least one storage system, an implementation of the interface for each of the plurality of storage systems, wherein at least one of the implementations of the interface is configured to process a plurality of requests, and a performance monitor configured to monitor performance of requests for at least one of a plurality of classes of requests.

Abstract: A method, computer system, and a computer program product for determining a composite similarity metric for data of a first data type is provided. The present invention may include providing a plurality of similarity metrics for the first data type. The present invention may also include providing a metric quantifying correlation of entities belonging to the first data type and entities belonging to a second data type. The present invention may then include developing a first regression model to predict values of the provided metric quantifying correlation of entities belonging to the first data type and entities belonging to the second data type using the provided plurality of similarity metrics. The present invention may further include calculating the composite similarity metric from a plurality of first regression coefficients in the developed first regression model.

Abstract: Mechanisms are provided for conducting a natural language dialogue between the automatic dialogue system and a user of a client computing device. An automatic dialogue system receives natural language text corresponding to a user input from the user via the client computing device, the natural language text having an ambiguous portion of natural language text. The automatic dialogue system analyzes user profile information corresponding to the user to identify an anomaly in the user profile information and predicts a user intent associated with the anomaly. The automatic dialogue system disambiguates the ambiguous portion of the natural language text based on the predicted user intent and generates a response to the user input based on the disambiguated natural language text which is output to the client computing device to thereby conduct the natural language dialogue.

Abstract: Mechanisms are provided for customizing responses to future questions based on identified anomalies in user profile information. An automated dialogue system monitors information associated with a plurality of entities, where the information includes quantities for variable values associated with the entities. The automated dialogue system, in response to determining that a quantity of a variable value associated with an entity in the plurality of entities has changed by an amount equal to or exceeding a corresponding threshold value, generates response information associated with a quantity of the variable value and an entity to respond to at least one future question. In addition, the automated dialogue system stores the responsive information in association with the entity for later retrieval in response to initiation of a dialogue session with the automated dialogue system. Time thresholds may be established for determining when to stop using the responsive information for responding to questions.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for a naming convention reconciler. A computer receives and pre-processing first dictionary 114 and second dictionary 116. In addition, the computer parses the pre-processed dictionaries to extract one or more names from each of the two dictionaries. The computer then generates a hash table of the names extracted from the second dictionary and searches the hash table for names that include a word in common with a name extracted from first dictionary 114. Based on identifying a name in the hash table that includes a word in common with a name extracted from first dictionary 114, the computer determines a similarity between the names and stores an association between the names having a greatest similarity.

Abstract: A computer-implemented method protects stack memory by moving contents of stack memory to an accumulation general purpose register. One or more processors identify an authorized function and a malicious function in a computer program, in which the malicious function is able to execute a call that provides the malicious function with access to stack memory that is used by the authorized function. The processor(s) move data from the stack memory to a protected kernel register before the call is executed, and store results of execution of the authorized function in a first register that is accessible only to the authorized function. The processor(s) then clear the stack memory, and move the results of execution of the authorized function from the first register to an accumulation general purpose register that is also accessible only to the authorized function.

Abstract: Techniques for maintaining high availability servers are disclosed. For example, a method comprises the following steps. One or more client requests are provided to a first server for execution therein. The one or more client requests are also provided to a second server for storage therein. In response to the first server failing, the second server is configured to execute at least one client request of the one or more client requests provided to the first server and the second server that is not properly executed by the first server.

Abstract: Mechanisms are provided for customizing responses to future questions based on identified anomalies in user profile information. An automated dialogue system monitors information associated with a plurality of entities, where the information includes quantities for variable values associated with the entities. The automated dialogue system, in response to determining that a quantity of a variable value associated with an entity in the plurality of entities has changed by an amount equal to or exceeding a corresponding threshold value, generates response information associated with a quantity of the variable value and an entity to respond to at least one future question. In addition, the automated dialogue system stores the responsive information in association with the entity for later retrieval in response to initiation of a dialogue session with the automated dialogue system. Time thresholds may be established for determining when to stop using the responsive information for responding to questions.

Abstract: Mechanisms are provided for conducting a natural language dialogue between the automatic dialogue system and a user of a client computing device. An automatic dialogue system receives natural language text corresponding to a user input from the user via the client computing device, the natural language text having an ambiguous portion of natural language text. The automatic dialogue system analyzes user profile information corresponding to the user to identify an anomaly in the user profile information and predicts a user intent associated with the anomaly. The automatic dialogue system disambiguates the ambiguous portion of the natural language text based on the predicted user intent and generates a response to the user input based on the disambiguated natural language text which is output to the client computing device to thereby conduct the natural language dialogue.

Abstract: Mechanisms are provided for conducting a natural language dialogue between the automatic dialogue system and a user of a client computing device. An automatic dialogue system receives natural language text corresponding to a user input from the user via the client computing device, the natural language text having an ambiguous portion of natural language text. The automatic dialogue system analyzes user profile information corresponding to the user to identify an anomaly in the user profile information and predicts a user intent associated with the anomaly. The automatic dialogue system disambiguates the ambiguous portion of the natural language text based on the predicted user intent and generates a response to the user input based on the disambiguated natural language text which is output to the client computing device to thereby conduct the natural language dialogue.

Abstract: Mechanisms are provided for conducting a natural language dialogue between the automatic dialogue system and a user of a client computing device. An automatic dialogue system receives natural language text corresponding to a user input from the user via the client computing device, the natural language text having an ambiguous portion of natural language text. The automatic dialogue system analyzes user profile information corresponding to the user to identify an anomaly in the user profile information and predicts a user intent associated with the anomaly. The automatic dialogue system disambiguates the ambiguous portion of the natural language text based on the predicted user intent and generates a response to the user input based on the disambiguated natural language text which is output to the client computing device to thereby conduct the natural language dialogue.

Abstract: Mechanisms are provided for customizing responses to future questions based on identified anomalies in user profile information. An automated dialogue system monitors information associated with a plurality of entities, where the information includes quantities for variable values associated with the entities. The automated dialogue system, in response to determining that a quantity of a variable value associated with an entity in the plurality of entities has changed by an amount equal to or exceeding a corresponding threshold value, generates response information associated with a quantity of the variable value and an entity to respond to at least one future question. In addition, the automated dialogue system stores the responsive information in association with the entity for later retrieval in response to initiation of a dialogue session with the automated dialogue system. Time thresholds may be established for determining when to stop using the responsive information for responding to questions.

Abstract: A method, computer system, and a computer program product for estimating error in predictions from a data model is provided. The present invention may include providing at least one first metric quantifying similarity of entities belonging to a first data type. The present invention may also include providing a second metric quantifying correlation of entities belonging to the first data type and entities belonging to a second data type. The present invention may then include developing a first model for predicting the second metric based on the at least one first metric. The present invention may further include developing a second model to estimate error in the first model.

Abstract: A method, computer system, and a computer program product for analyzing data belonging to a plurality of data types wherein data belonging to a first data type of the plurality of data types may be correlated with data belonging to a second data type of the plurality of data types is provided. The present invention may include providing at least one first metric quantifying similarity of entities belonging to the first data type. The present invention may then include providing a second metric quantifying correlation of entities belonging to the first data type and entities belonging to the second data type. The present invention may also include inferring a value of the second metric correlating a first entity of the first data type with a second entity of the second data type.

Abstract: A method, computer system, and a computer program product for determining a composite similarity metric for data of a first data type is provided. The present invention may include providing a plurality of similarity metrics for the first data type. The present invention may also include providing a metric quantifying correlation of entities belonging to the first data type and entities belonging to a second data type. The present invention may then include developing a first regression model to predict values of the provided metric quantifying correlation of entities belonging to the first data type and entities belonging to the second data type using the provided plurality of similarity metrics. The present invention may further include calculating the composite similarity metric from a plurality of first regression coefficients in the developed first regression model.

Abstract: Mechanisms are provided for conducting a natural language dialog between the automatic dialog system and a user of a client computing device. An automatic dialog system receives natural language text corresponding to a user input from the user via the client computing device, the natural language text having an ambiguous portion of natural language text. The automatic dialog system analyzes user profile information corresponding to the user to identify an anomaly in the user profile information and predicts a user intent associated with the anomaly. The automatic dialog system disambiguates the ambiguous portion of the natural language text based on the predicted user intent and generates a response to the user input based on the disambiguated natural language text which is output to the client computing device to thereby conduct the natural language dialog.

Abstract: A system for monitoring a plurality of storage systems includes an interface specifying a set of methods for using at least one storage system, an implementation of the interface for each of the plurality of storage systems, wherein at least one of the implementations of the interface is configured to process a plurality of requests, and a performance monitor configured to monitor performance of requests for at least one of a plurality of classes of requests.

Abstract: A computer-implemented method protects stack memory by moving contents of stack memory to an accumulation general purpose register. One or more processors identify an authorized function and a malicious function in a computer program, in which the malicious function is able to execute a call that provides the malicious function with access to stack memory that is used by the authorized function. The processor(s) move data from the stack memory to a protected kernel register before the call is executed, and store results of execution of the authorized function in a first register that is accessible only to the authorized function. The processor(s) then clear the stack memory, and move the results of execution of the authorized function from the first register to an accumulation general purpose register that is also accessible only to the authorized function.

Abstract: A computer-implemented method protects stack memory from a malicious function. One or more processors identify a first function and a second function in a computer program, where the first function is an authorized function and the second function is a malicious function. The processor(s) determine that the second function is able to execute a call that provides the second function with access to a stack memory that is used by the first function. The processor(s) move data from the stack memory to a protected kernel register, which is accessible only to the first function, before the call is executed.

Abstract: A request is received for personal data associated with a user from an application. One or more policies are established for release of the requested personal data. The requested personal data is provided to the application in encrypted form. One or more decryption keys are then sent to the application in accordance with the established policies, the one or more decryption keys being utilizable for decrypting the encrypted personal data.