International Business Machines Corporation

Rahamim Katan

Fan Jing Meng

Jia Qi Li

Amith Singhee

Gary Mazo

David Scott Wenk

Yan Luo

Saravanan Krishnan

Zhi Shuai Han

Hongxia Li

Monvorath Phongpaibul

Tala El Hallak

Vini Kanvar

Stanislav Georgiev

Techniques for context-based keyword grouping for business rule mining are described herein. An aspect includes determining, based on a first corpus, a first list of keywords. Another aspect includes constructing a co-occurrence matrix based on the first list of keywords. Another aspect includes applying a clustering algorithm to the co-occurrence matrix to determine a first plurality of keyword groups. Another aspect includes presenting the first plurality of keyword groups to a user via a user interface.

Context-based keyword grouping

A computer-implemented method includes receiving, by a processor, real time operation data related to an application, identifying components of the application based on the operation data, extracting relationships and interdependencies between the components, and generating a graph of the identified components, the relationships and the interdependencies. The method also includes determining one or more dynamic metrics of the identified components, the one or more dynamic metrics indicative of interactions between the components, extracting statistical information describing at least one of performance and resource consumption based on the operation data, incorporating the dynamic metrics into the graph, determining a behavior of at least one component based on a pattern of appearance of the at least one component in the graph, and generating a model of the application based on the identified components and the determined behaviors.

Evaluation of dynamic relationships between application components

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Modiin, Israel

Rahamim Katan