Accenture Global Solutions Limited

Ranjana Bhalchandra Narawane

Srikanth G Rao

Dongay Choudary Nuvvula

Tarun Singhal

Sanjay Tiwari

Nithyanandan Periasamy Dhanapal

Surya Kumar Venkata Gangadhara Idumudi

Avishek Gulshan

Shubhashis Sengupta

Sanjay Podder

Roshni Ramesh Ramnani

Badarayan Panigrahi

Surya Kumar Ivg

Vinay Avinash Dorle

Tarang Kumar

Manu Khanna

Sumitraj Ganapat Patil

Suchit Vishnupant Bhatwadekar

Tirupal Rao Ravilla

Amar Ratanlal Bafna

Rakesh Thimmaiah

Gauri S Chikodi

Devendra Singh Dhakarey

Devendra Gautam

Nikhil Varshney

Shiv Kumar

Soumya Chandran

Vinay Avinash Dorie

Rati Rajendra Mangal

Uday Varma

Dinesh Chandar Vasudevan

An interactive query processing system provides a user interface, including a 'chat bot,' capable of receiving natural language queries from users, processing those queries to determine intents and entities, extracting data from applications and portals, synthesizing the data, and displaying the data to the user via the user interface in a useful, easy to understand, and unified format. The user utilizes a singular UI to receive data responsive to queries rapidly instead of manually extracting and synthesizing data from multiple different portals or dashboards. Additionally, the system provides actionable insights without requiring a user to sort or analyze data from multiple sources.

System architecture for interactive query processing

A multimedia content distribution system can receive and store multimedia content items from content providers. The system may also receive and store content distribution information from a variety of different data sources that is related to the multimedia content items and the distribution of the multimedia content items. The system may predict viewership for a multimedia content item for future release dates based on the content distribution information, and provide automated control of the distribution of the multimedia content item, which may include distribution over a content distribution network.

Multimedia content distribution and recommendation system

Methods and systems including computer programs encoded on a computer storage medium, for receiving a request for digital content to be provided from a plurality of items of digital content, determining a set of content scores for each item of digital content in the plurality of items of digital content, each content score in the set of content scores being specific to a user of the plurality of users, and a respective item of digital content, calculating a combined score deviation for each item of digital content based on a difference between a minimum content score and a maximum content score of the set of content scores of a respective item of digital content, determining at least one candidate item of digital content, the at least one candidate item of digital content having a lowest combined score deviation among combined score deviations of the plurality of items of digital content, and providing the at least one candidate item of digital content.

Intelligent content recommender for groups of users

An intelligent VR (IVR) system receives a VR content item and automatically augments the VR content item with additional or ancillary content. The intelligent VR system initially identifies within the VR content item, valid textual and non-textual objects that have ancillary content associated therewith. The IVR system provides hotspots that signify presence of the ancillary content for the valid objects during a display of the VR content item. The hotspots and the ancillary content are positioned for display corresponding to pixel blocks including the valid objects. The ancillary content is selected for the hotspots based on a spatial and temporal extent of display of the valid objects. The hotspots with respective ancillary content items and the VR content item are streamed to a head mounted display (HMD) for display to a viewer.

Intelligent object recognizer

A device receives first network information associated with a first portion of a network, and second network information associated with a second portion of the network, and determines, based on the first network information and the second network information, an alarm condition for the network. The device determines, based on correlation rules, whether the alarm condition relates to a currently handled alarm condition or a previously handled alarm condition. The device correlates the alarm condition with network inventory information, network topology information, and network service information, when the alarm condition does not relate to the currently handled alarm condition or the previously handled alarm condition, to generate a correlated alarm condition. The device automatically generates a resolution for the correlated alarm condition based on the correlated alarm condition, and automatically performs one or more actions based on the resolution for the correlated alarm condition.

Automatic monitoring, correlation, and resolution of network alarm conditions

A system for migrating data from a legacy system to a target system includes an input/output (IO) processor configured to receive legacy data from a plurality of different types of legacy systems and to communicate target data to a plurality of different types of target systems; a staging area database configured to store legacy data according to a common database schema; a localized database configured to store target data according to a target schema that is associated with a target system type; a processor in communication with the interface, the staging area database, and the localized database; and non-transitory computer readable media in communication with the processor that stores instruction code. The instruction codes is executed by the processor and causes the processor to: determine a target schema associated with a target system type; convert the legacy data stored in the staging area database to localized data according to the determined target schema; store the localized data in the localized database; and communicate the localized data to the target system.

Data migration system

Methods and systems including computer programs encoded on a computer storage medium, for interactive content recommendation. In one aspect, a method includes receiving a request for content by a user, determining a user intent based on the received request, providing to the user a first attribute responsive to the user intent, receiving a first attribute value responsive to the first attribute, providing a second attribute, and receiving a second attribute value responsive to the second attribute. A particular content vector including a first content attribute and a second content attribute for a particular content item is identified where the first content attribute and the second content attribute sufficiently match the first attribute value and the second attribute value. The particular content item is provided as a suggested content item, and, responsive to a user selection of the particular content item, provided for presentation on the user device.

Intelligent humanoid interactive content recommender

A system may receive, from multiple data providers or multiple platforms, data associated with content, a content provider that provides the content, and multiple channels via which the content is provided or consumed. The data may include first data, received from a first data provider or a first platform, that is associated with a different file type than second data received from a second data provider or a second platform. The system may include a data model associated with the first data and the second data. The system may aggregate the data from the multiple data providers or the multiple platforms. The system may identify a relationship between the first data and the second data. The first data and the second data may be different types of data. The system may perform an action based on the relationship between the first data and the second data.

Automatically generating a recommendation based on automatic aggregation and analysis of data

A device may process application data or historical data to identify a set of metrics to be used to analyze a set of applications or to identify baseline values for the set of metrics. The device may determine a score, for each application of the set of applications, based on values for the set of metrics for the each application of the set of applications. The device may determine a refined classification for the each application of the set of applications based on the historical data or information related to the classification or the score. The device may generate a set of recommendations related to optimizing a current deployment of the set of applications. The device may perform an action to implement the set of recommendations related to optimizing the current deployment of the set of applications.

Efficiency of computing resource consumption via improved application portfolio deployment

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Mumbai, India

Ranjana Bhalchandra Narawane