Oracle International Corporation

Netsuite Inc.

Vodafone IP Licensing Limited

Oleksiy Ignatyev

Mihail Mihaylov

Gary Alan Wiessinger

Mihail Lambrinov Mihaylov

Volkmar Scharf-Katz

Kevin Tristan Scarr

Celestine Star Grady Smith

Simon Clark

Donna Fung

Mihir Bharatkumar Shah

Ondrej Bohaciak

Douglas P Solomon

Joseph Fung

Operations include determining whether to cache resources accessed by a query based on the execution time of the query. The system identifies a set of executions of a same query. The system determines a cumulative execution time for the set of executions of the same query. If the cumulative execution time exceeds a threshold value, then the system caches a resource used for execution of the query.

System and method for query resource caching

Systems, methods, and other embodiments that perform data synchronization in a cloud computing environment are described. In one embodiment, a method includes maintaining a plurality of accounts within a cloud computing environment. In response to receiving a command to enable data synchronization for an account, a data synchronization condition is constructed to specify that a synchronization action will be triggered when data input by the account satisfies the data synchronization condition. Access to the account is monitored. In response to the access satisfying the data synchronization condition, the synchronization action is triggered to identify a second account with data corresponding to data input by the account. The synchronization action is executed to create a synchronization field in the second account and insert data of the account into the synchronization field.

Data synchronization in a cloud computing environment

A system and associated processes to allocate tenants to servers are disclosed. A set of vectors corresponding to a plurality of tenants to be allocated is generated. A target vector establishing a target value of a sum of vectors allocated to a first server is determined. A first vector included in the set of vectors that satisfies a defined relationship with the target vector is identified, and in response, a tenant corresponding to the first vector is allocated to the first server. It is determined whether a second vector satisfies a defined relationship with both the target vector and the first vector exists. If so, a tenant corresponding to the second vector is allocated to the first server. If not, the tenant corresponding to the second vector is allocated to a second server that is different from the first server.

System and methods for optimal allocation of multi-tenant platform infrastructure resources

A defect level for a software application may be predicted by training a model using aspects of development processes from previous software applications as training data. Aspects of previous software development processes may be aggregated to form signal vectors for each deployed application. Defect scores calculated from actual defects in the deployed software applications may be paired with the corresponding development signal vectors. The signal vectors and calculated defect scores may act as training data and labels for a predictive model that uses lasso regression to generate a predicted defect score during the development process. A signal vector for a current development process may be updated in real time as the software is developed to update a predicted defect score and provide a subset of aspects in the signal vector that contribute most to the score such that actions may be taken to improve the score.

Software defect prediction model

Operations include estimating, in real time, a runtime of a query. The query optimization system receives set of query definitions for defining a target query. The system uses the set of query definition elements to determine an estimated runtime for the target query. If the estimated runtime exceeds some acceptable threshold value, then the system determines a modification to the set of query definition elements. The system uses the modification to generate a modified query, corresponding to a lower estimated runtime.

Estimated query performance

Systems, methods, and other embodiments associated with providing automated discovery and facilitation of user business processes are described. Parse a system log of an integrated business system to identify interactions of a user with each event of a selected type of event. For each event, create a data structure that describes the interactions with the event based on the identified interactions and one or more characteristics of the event. Analyze the data structures to train a machine learning model to apply a process applied to events of the selected type by the user. Generate a customized user interface that is configured to present the user with an option to automatically carry out the process for a set of subsequent events of the selected type based on application of the model. Substitute the customized user interface for a standard user interface when transmitting instructions to display one or more subsequent events.

Automated process discovery and facilitation within a cloud business application

Systems and methods to infer or predict the proper placement of unstructured data (such as text, phrases, segments of phrases, alphanumeric characters) into a more structured format (such as a specific data field). In some embodiments, this is based on a user's prior assignment of similar unstructured data into a specific structure. In some embodiments, this may be based on other users' prior assignment of similar unstructured data into the specific structure. In yet other embodiments, this may be based on information obtained from business data used by a data processing platform to assist in operating the business (i.e., either business data or the output of a business application that processes the business data, such as an ERP, CRM, or eCommerce application).

System and methods of generating structured data from unstructured data

A system and associated processes to allocate tenants to platform resources are disclosed. A set of vectors corresponding to a plurality of tenants to be allocated is generated. A target vector establishing a desired value of a sum of vectors allocated to a first platform resource is determined. A first vector included in the set of vectors that satisfies a defined relationship with the target vector is identified, and a tenant corresponding to the first vector is allocated to the platform resource as a result. It is determined whether a second vector satisfies a defined relationship with both the target vector and the first vector exists. If so, a tenant corresponding to the second vector is allocated to the first platform resource. If not, the tenant corresponding to the second vector is allocated to a second platform resource, that is different from the first platform resource.

Systems, methods, and other embodiments associated with providing automated discovery and facilitation of user business processes are described. Parse a system log of a software platform to identify interactions of a user with each event of a selected type of event. For each event, create a data structure that describes the interactions with the event based on (i) the identified interactions and (ii) characteristics of the event. Analyze the data structures to create a model of a process applied to events of the selected type by the user. Generate a customized user interface of the software platform that includes a function configured to facilitate the process. Substitute the customized user interface for a standard user interface when displaying the subsequent events to a user.

A system and methods for generating an interaction-weighted visualization of an organization or group, with the relationships between members being based on or weighted by the amount, type, degree, or significance of interactions between them and the flow of communications between members, etc. In some embodiments, this may have the form of a tree structure with nodes representing employees being connected by branches. The size, color, or number of branches may indicate characteristics of the interactions between the connected nodes (e.g., the frequency, importance, or topic of the interactions, etc.). For some purposes this provides a more accurate and realistic view of how information and communications move within an organization. It may also be used to provide insight into the strength of certain relationships, the degree of involvement of certain people or groups in implementing policies or in making decisions, or the relative importance of certain communication channels.

System and methods for processing information regarding relationships and interactions to assist in making organizational decisions

The system receives user-selected fields from a set of candidate fields. Based on the user-selected fields, the system recommends at least one candidate field from the set of candidate fields. The system may select the at least one candidate field for recommendation based, at least in part, on a set of one or more prior queries. Responsive to receiving a user selection of a recommended candidate field, the system adds the recommended candidate field to the set of user-selected fields to obtain an updated set of user-selected fields. The system executes the query based on the updated set of user-selected fields.

Recommending fields for a query based on prior queries

A system and associated processes to enable a multi-tenant platform operator or administrator to make more optimal decisions with regards to the allocation of platform infrastructure resources (such as computational capabilities, data storage, etc.) among one or more tenants or accounts. In some embodiments, the inventive methods construct a data 'signature' for a set of identified users, accounts, or tenants, where the signature contains data regarding the user, account, or tenant's 'consumption' of platform infrastructure resources.

Systems, apparatuses, and methods for the automated detection of incorrect data during a data entry process or detecting incorrect data that has been entered and stored previously. In one embodiment, the invention utilizes one or more of statistical analysis or a machine learning technique (either supervised or unsupervised) in order to identify potentially incorrect data.

System and method for automated detection of incorrect data

Systems, apparatuses, and methods for determining one or more demographic characteristics of a user/customer, and then using such information to generate a recommendation of a product or service for the user/customer. In some embodiments, a customer's first and/or last name as obtained from a single transaction may be used to infer their nationality or ethnicity with a certain probability of being correct. This demographic information may then be used to identify one or more products or services that are expected to be of interest.

Growing community of inventors

Belmont, CA, United States of America

Oleksiy Ignatyev