Oracle International Corporation

Intuit, Inc.

Other

Govinda Sambamurthy

Rahul Goyal

Raji Sankar

Srivatsan Vijayaraghavan

Hari Charan Ramachandra Rao

Shyamalendu Tripathy

Ashwin Kumar Karkala

Anand Patil

Siben Nayak

Nishant Sehgal

Anil Kumar Sharma

Manish Jain

Sandeep Gupta

Sandeep Pandita

Satyajit Nath Bhowmik

Samar Ranjan

Anil Sharma

Anshika Pandita

Sirigiri Venkata Giri

Archit Singh

Harsh Madhogaria

Charu Garg

Jitin Maherchandani

Rohit Kumar

Chandrasekhar Atla

Shirish Peshwe

Sachin Gupta

Shirish K Peshwe

Nischith Bagivalu Manjegowda

Suraj Menon

Vipin Gupta

Chandraprakash Joshi

Saraswati Hedge

Divakar Ungatla

Vineet Dhanawat

Nivedita Nayak

Viswanath Pasupuleti

Jatin Mahajan

Vinay Kumar Jaasti

Namita Devadas

Apoorv Anand Vajpayee

An orchestration layer for execution user defined automation workflows. The orchestration layer may include multiple process instances that host user defined automation workflows that automate processes or tasks. To improve system performance and reduce operating costs, the user defined automation workflows are deployed to the orchestration layer in a standard format that standardizes the user defined workflow configurations. The orchestration layer may also dynamically scale the computational resources allocated to teach process instance based on the properties of each user defined automation workflow.

Orchestration layer for user defined automation workflows

A workflow construction system for constructing automation workflows that automate user specific processes. The workflow construction system may include a template library including workflow templates and pre-configured attributes. The workflow template can accelerate the design and construction of custom automation workflows. An orchestration layer included in the workflow construction system will also improve the performance of systems that execute the automation workflows by dynamically scaling the processing capacity, memory, and storage of servers and other systems hosting the model file instances of the automation workflows to ensure the available resources meet the demands of users completing processes using the automation workflows.

Methods and systems for building custom automation workflows

Systems and methods for identifying recommended topics are disclosed. An example method may be performed by one or more processors of a system and include identifying one or more attributes of a system user, identifying a subset of topics relevant to the system user based on analyzing the one or more attributes of the system user using an analysis model trained with a machine learning process to identify relevant topics for system users based on historical user attributes, generating, for each respective topic of the subset of topics, using the trained analysis model, a relevance score for the respective topic based at least in part on a most recent system page previously accessed by the system user and a current system page accessed by the system user, and generating one or more recommended topics for the system user based on the relevance scores.

Method and system for providing personalized presearch for users of a data management system

A processor may launch a common layer including a browser and a shell. The processor may identify a request for data required by the software platform. The processor may determine a context in which the request was generated by detecting, by the shell, whether the software platform is an on-premise solution or a cloud solution; examining, by the shell, the request to determine whether it requires local resources or cloud-based resources; and designating, by the shell, the context as a cloud-based context or an on-premise context based on the detecting and the examining. In response to the determining, the processor may perform processing related to a request generated in the on-premise context using at least one local resource stored in a local data store; and communicate, by the browser, with at least one cloud-based resource to perform processing related to a request generated in the cloud-based context.

Experience convergence for multiple platforms

Methods and systems for building custom automation workflows to integrate multiple applications

Disclosed herein are systems and methods for replicating data across deployments in a routing constrained environment. To replicate data, a processor may detect a modification that changes data for a source entity within a source environment hosting a source deployment of an application. The processor may then update a target environment hosting a target deployment of the application to mirror the modification within the source environment. To update the target environment, the processor may generate a mapping artifact that identifies the source entity having changed data and the target entity within the target environment receiving the changed data. The processor may then create a mapping infrastructure including one or more compute instances that replicate the changed data for the source entity in the target entity. To replicate data, the one or more compute instances may execute a mapping script that replicates the changed data from the source entity in the target entity by copying changed data from the source environment and writing it to a database in the target environment.

Replicating data across deployments in a routing constrained environment

A method and system provides personalized self-help assistance to users of a data management system. The method and system trains an analysis model to identify relevant assistance topics based personal attributes of the user and contextual attributes associated with the user. The method and system outputs personalized assistance topics recommendation data to the user based on the analysis of the analysis model.

An aspect of the present disclosure facilitates users of touch screens to conveniently provide values for fields of a form. In an embodiment, a mapping is maintained to map symbols to corresponding profiles, with each profile being defined to specify a respective value for each of a corresponding set of fields. A form is sent for display on a touch screen, and a user is permitted to perform a touch action constituting a sequence of touch points (and representing input symbol) on the touch screen. The mapping is examined to determine a first symbol matching the input symbol, and a first profile corresponding to the first symbol is identified. The form is then auto-filled with values specified by the first profile. The user can continue interaction with the form with such auto-filled values.

Entry of values into multiple fields of a form using touch screens

An aspect of the present invention provides for capturing of audit trail data related to processing of requests. In an embodiment, the received requests are classified into a first category and a second category. For each request in the first category, the corresponding audit trail data is stored directly into non-volatile storage upon processing of the request. On the other hand, for each request in the second category, the audit trail data is first stored into a volatile memory upon processing of the request, and then later copied from the volatile memory to non-volatile storage. Thus, the audit trail data corresponding to both categories of requests is eventually available stored on non-volatile storage.

Model for capturing audit trail data with reduced probability of loss of critical data

A mechanism for efficient collection of data is described for runtime middleware environments. Two frequencies are used, a collection frequency (CF) to collect the data and an aggregation frequency (AF) to aggregate and persist the data in a repository. The collection cycle is a shorter time interval than the aggregation cycle. An agent residing in the container periodically collects a set of data upon every collection cycle from the components of the middleware system and caches the set of data locally. Upon every aggregation cycle, the agent applies an aggregation function to the collected set of data and persists the set of data into a repository after the aggregation function has been applied. The aggregation function is such that it resulting data represents the behavior of the runtime environment in the total duration of the aggregation cycle.

Efficient data collection mechanism in middleware runtime environment

A system and method for detecting an outlier in a usage pattern comprises a computer accessible to perform an operation. The system includes an audit forensics engine having an outlier detection module. When an instance occurs where the operation is performed, audit trail data is captured related to the operation. The outlier detection module determines for the instance where the operation is performed whether the instance is an outlier in a usage pattern based on a comparison of the audit trail data to the usage pattern.

System and method of automatically detecting outliers in usage patterns

Feature and deployment recommendation systems and methods for content management systems comprises a vendor-site deployment and one or more customer-site deployments. The vendor-site deployment is configured to recommend an adaptation of any of the one or more customer-site deployments. The vendor-site deployment including a customer configuration repository adapted to store content usage metrics received from one or more customer-site deployments, an analytical engine configured to generate content usage patterns based on the stored content usage metrics, and a recommendation engine configured to recommend the adaptation.

Feature and deployment recommendation systems and methods for content management systems to provide recommendations for enhanced feature usage based on usage patterns

A method of determining a root cause of a performance problem is provided. The method comprises analyzing a plurality of performance indicators/metrics in a first time period and determining that at least one performance indicators/metric is exhibiting abnormal behavior. The method further comprises analyzing the plurality of performance indicators/metrics over a second time period, the second time period is longer than the first time period, and determining trend information for each performance indicators/metric over the second time period. The method further comprises correlating the trend information for each performance indicators/metric with performance problem information stored in a knowledge base, identifying a potential cause of the abnormal behavior based on the correlation, and alerting a user of the potential cause.

System and method for determining causes of performance problems within middleware systems

In specific embodiments, a content management system operable on one or more microprocessors comprises a content repository storing a plurality of content items and a content usage analyzer. The computer is usable to perform one or more operations on one or more contents items stored in the content repository, and when an operation is performed on a content item, audit data is captured related to the operation. The content usage analyzer is configured to identify an idle content item within the content repository based on the captured audit data.

Content management system and method of managing retention and disposition of content items

Systems and methods are described for diagnosing behavior of software components in an application server. The application server can comprise a plurality of components that process incoming requests. A diagnostics advisor can be deployed with the application server and can determine an efficiency and/or inefficiency of each of the components of the application server or other middleware system. The efficiency determined by computing a ratio of the number of requests that completed execution during a particular sampling time period to the number of requests that were received. The inefficiency is the ratio of the number of requests that are still being executed at the end of the sampling time period to the number of requests that were received. The diagnostics advisor employs the determined efficiency and/or inefficiency to diagnose a misbehavior or other problem of the components in the application server.

Method of measuring and diagnosing misbehaviors of software components and resources

Growing community of inventors

Bengaluru, India

Govinda Sambamurthy