Xerox Corporation

Conduent Business Services, LLC

Other

Tridib Mukherjee

Gueyoung Jung

Shruti Kunde

Koustuv Dasgupta

Sujit Gujar

Sharanya Eswaran

Partha Dutta

Sakyajit Bhattacharya

Avinash Sharma

Shisagnee Banerjee

Varun Sharma

Todd Redmond

Aditya Hegde

Shanmuga-Nathan Gnanasambandam

Jean-Pierre R M Van De Capelle

Deepthi Chander

Manjira Sinha

Anirban Mondal

Avantika Gupta

Haengju Lee

Saraschandra Karanam

Preethy Varma

Mahima Suresh

Satarupa Guha

Mridula Singh

Datasets relating time information to crime occurrences in the geographical regions are received. Time based crime patterns are extracted. Based on similarities among the crime patterns, the geographical regions are clustered. A selected time series dataset is augmented with a second time series dataset from the same cluster. Based on the augmented time series dataset, a new crime pattern is extracted. Based on the new crime pattern, a crime forecast is made for the selected geographical region.

Crime analysis using domain level similarity

The disclosed embodiments illustrate a method and a system for managing crowd-sensed data, associated with events occurring in a geographical area. The method includes receiving crowd-sensed data from one or more data sources, wherein the crowd-sensed data comprises one or more event reports associated with at least a type of each of one or more events reported by the one or more data sources. The method further includes generating a data structure based on an aggregation of the received crowd-sensed data. Further, the method includes determining first information and second information based on at least the generated data structure, a reputation score of each of the one or more data sources and metadata associated with each of the one or more event reports. The method further includes displaying at least the determined first information and second information based on at least a prioritization of the one or more events.

Method and system for managing crowd-sensed data

A crime analysis system, method, and apparatus comprising at least one processor and a storage device communicatively coupled to the at least one processor, the storage device storing instructions which, when executed by the at least one processor, cause the processor to perform operations comprising receiving information provided by one or more data collection source, storing the information, wherein the stored information is formatted, processing the information to generate crime clustering data associated with at least one region and at least one crime, processing the crime clustering data associated with at least one region and at least one crime to generate benchmarking of the at least one region with at least one other region, and providing crime clustering data associated with at least one region and at least one crime, and benchmarking of the at least one region with at least one other region for presentation through a user interface.

Mixture model based time-series clustering of crime data across spatial entities

A method and a system for recommendation of a succession of one or more services for a service workflow are disclosed. In an embodiment, a query is received to retrieve one or more services from a repository of a plurality of services stored in a hierarchical structure. The hierarchical structure comprises a plurality of hierarchical levels, each hierarchical level in the plurality of hierarchical levels comprising a set of nodes. Each node in the set of nodes in each hierarchical level, stores a first semantic information and a second semantic information. Further, the query is compared with the first semantic information and the second semantic information associated with a first node. The first node or the second node is selected based on the comparison. Further, the first set of services or the combination of services, associated with the selected node is recommended, as the service workflow, to the user.

Method and system for recommendation of a succession of one or more services for a service workflow

Performing semantic analysis on a user-generated text string includes training a neural network model with a plurality of known text strings to obtain a first distributed vector representation of the known text strings and a second distributed vector representation of a plurality of words in the known text strings, computing a relevance matrix of the first and second distributed representations based on a cosine distance between each of the plurality of words and the plurality of known text strings, and performing a latent dirichlet allocation (LDA) operation using the relevance matrix as an input to obtain a distribution of topics associated with the plurality of known text strings.

Performing semantic analyses of user-generated textual and voice content

Methods and systems are disclosed for providing cloud services to multiple customers in a cloud. One embodiment includes receiving a number of requests for the cloud services from the multiple customers simultaneously or substantially simultaneously; prioritizing the requests based on a probability distribution of actually deploying a service, a budget of the customers, and an expected demand of the requested service based on the probability distribution; generating a number of cloud configurations along with a number of Service Level Agreements (SLAs) for the customers based on prioritization of the requests, a class & past behavior of the customers, and a current demand of the cloud services, the SLAs of the customers include differentiated price offering; recommending the cloud configurations and the SLAs to the customers; allowing the customers to negotiate terms of the SLAs; and providing the cloud services based on the negotiated SLAs to the customers.

Methods and systems for regulating service layer agreements for multiple cloud service requests

A method and a system for recommending services to a requestor over a communication network. A request comprising one or more keywords and one or more service level agreements (SLAs), is received from a requestor computing device over the communication network, to process one or more tasks. One or more first services from one or more available services are selected based on the request. For a first service from the one or more first services, a first score and a second score is determined. The one or more first services are ranked based on the first score and the second score. A recommendation of the one or more first services is transmitted to the requestor based on the ranking.

Method and system for recommending services to requestors

Methods and systems for determining prices of customized virtual machines required to process customer-specified workloads are disclosed. A count of instances of the customized virtual machines, required to process the customer-specified workloads is determined, based on a configuration of the customized virtual machines. The instances of the customized virtual machines are consolidated on virtual machine servers. Further, the prices of the customized virtual machines are determined based on a count of the virtual machine servers, unused resources in the virtual machine servers, and unused resources in the customized virtual machines. The determined prices are recommended to the customer. Further, at least one of the prices of the customized virtual machines or the configuration of at least one or more customized virtual machines is modified, based on a response to the recommendation received from the customer.

Methods and systems to price customized virtual machines

A method and system to determine a computational resource requirement is described. The method and system rank one or more computational resources for each of the plurality of tasks in an ascending order, based on a cost associated with the plurality of tasks for each of the computational resource. Based on the ranked one or more computational resources and a fairness metric, the method and system allocates the one or more capacity units associated with the computational resource to perform the plurality of tasks. The method and system determines the computational resource requirement to perform the plurality of tasks based on the allocated one or more capacity units. The fairness metric ensures that allocation of the one or more capacity units to the plurality of tasks is performed in a manner to maximize the fairness.

Methods and systems for determining computational resource requirement

A method provides a recommendation for a cloud configuration for deploying a service. In response to receiving a service request, a database is searched for a cloud configuration. The search is performed by acquiring a resource usage pattern for the service. The resource usage pattern is mapped to a multidimensional space, which is searched for a previously deployed cloud configuration having a similar resource usage pattern. In response to finding a previously deployed cloud configuration, the activity management is determined for the previously deployed cloud configuration. A recommendation is made based on the activity management.

System and process to recommend cloud service cloud configuration based on service similarity

Methods and systems for creating one or more statistical classifiers. A first set of performance parameters, corresponding to the one or more applications and the one or more computing infrastructures, is extracted from a historical data pertaining to the execution of the one or more applications on the one or more computing infrastructures. Further, a set of application-specific and a set of infrastructure-specific parameters are selected, from the first set of performance parameters, based on one or more statistical techniques. A similarity between each pair of the applications, each pair of the computing infrastructures, and each pair of possible combinations of an application and a computing infrastructure is determined. One or more statistical classifiers are created, based on the determined similarity.

Methods and systems for determining inter-dependenices between applications and computing infrastructures

Methods and systems for sharing computational resources. A request from a first node is received for the one or more computational resources. The request comprises a service level agreement (SLA) associated with the requested one or more computational resources. The request is compared with one or more advertisements sent by at least two second nodes, other than the first node. The one or more advertisements correspond to an availability of a set of computational resources associated with each of the at least two second nodes. A portion of computational resources from the set of computational resources associated with each of the at least two second nodes is allocated to the first node, based on the comparison, such that a combination of the portion of computational resources satisfy the SLA associated with the request.

Methods and systems for sharing computational resources

Embodiments of a method are disclosed for computing trust index among multiple entities associated with a resource marketplace. The method includes receiving multiple inputs including interaction attributes, attribute importance factors, references to databases, and multiple entities associated with the resource marketplace. The method also includes creating a weighted-interaction graph based on the received inputs. The weighted-interaction graph includes multiple vertices representing the entities. The method further includes performing a topology-specific analysis of the weighted-interaction graph. The method furthermore includes computing Euclidean distances for each pair of vertices in the weighted-interaction graph based on the performed analysis. The method also includes determining a trust index for a first entity in the received multiple entities based on the computed Euclidean distances. The trust index includes ranking of at least one of the multiple entities with respect to the first entity. The ranking is inversely proportional to the computed Euclidean distances.

Methods and apparatuses for trust computation

Disclosed are the methods for scheduling a task including at least one sub-task, on one or more computing devices in a distributed computing environment. A set of computing devices are identified from the one or more computing devices, based on an availability of a set of computational resources on the set of computing devices. Each computing device in the set of computing devices is ranked based on at least one of a monetary cost or a network cost, associated with the execution of the at least one sub-task on the each computing device. The at least one sub-task is allocated to at least one computing device from the set of computing devices for execution based on at least one of the ranking or an acceptable success probability associated with the execution of the at least one sub-task.

Methods and systems for scheduling a task

Methods and systems for recommending one or more computational resources. A portion of computational resources is determined from a set of computational resources associated with a datacenter based on a user-profile associated with a user, from one or more users, and the set of computational resources. The user-profile comprises at least one of a required performance level, a required load, or a cost constraint. The one or more computational resources are recommended from the portion of computational resources, in response to requests received from the one or more users.

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Bengaluru, India

Tridib Mukherjee