International Business Machines Corporation

Leonid Gorelik

Yifat Yulevich

Alexander Pyasik

Josemina Marcella Magdalen

Anand Ranganathan

Oded Sofer

Guy Galil

Abraham Hochmann

Evgeny Chernis

Dmitry Shusterman

Examples of techniques for generating streaming analytics applications are described herein. An example computer-implemented method includes receiving, via a processor, subject matter requirements in a semi-structured format. The method includes classifying, via the processor, the subject matter requirements based on a predefined taxonomy. The method includes extracting, via the processor, a list of entities from the subject matter requirements based on grammar. The method includes generating a solution based on a glossary and the list of extracted entities. The method includes generating, via the processor, a streaming analytics application based on the solution.

Generating streaming analytics applications using a glossary

Techniques for informing a user about an agreement including agreement terms and trustworthiness of data source are described herein. In some examples, a processor receives agreement document data while the data is in route to a client device. A system receives network sources and content data of the agreement document. The network sources are to be processed by the processor with traffic analytics, and the content data is to be processed with text analytics. The output of these analytics is used to generate an agreement risk event for delivery to the client device with the original agreement document data.

Real-time agreement analysis

Examples of techniques for detecting and preventing sensitive information leaks are described herein. In one example, a method for detection of sensitive information leaks comprises computing, via a processor, a set of rules that identify sensitive information, and sending, via the processor, the set of rules to a dispatcher application using a protocol. The method can also include detecting, via the processor, that at least one data block of the transmitted data matches the set of rules, and executing, via the processor, a corrective action in response to detecting that at least one of the transmitted data blocks matches the set of rules.

Detection and prevention of sensitive information leaks

Examples of techniques for detecting and preventing sensitive information leaks are described herein. In one example, a method for detection of sensitive information leaks includes computing, via a processor, a set of rules that identify sensitive information, and sending, via the processor, the set of rules to a dispatcher application using a protocol. The method can also include detecting, via the processor, that at least one data block of the transmitted data matches the set of rules, and executing, via the processor, a corrective action in response to detecting that at least one of the transmitted data blocks matches the set of rules.

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Petach Tikva, Israel

Leonid Gorelik