The present invention relates to summarizing cross-network user behavioral data. The summarizing cross-network user behavioral data may particularly include publishing the data to one or more data structures that become accessible to a server hosting an authorized domain when a user accesses the authorized domain.

A method for gender recognition of a user and related products are provided. The method includes the following. A sever receives user characteristic data from a mobile terminal, where the user characteristic data is indicative of usage of the mobile terminal by the user. At least one user characteristic data sample matching the user characteristic data is determined from a predetermined set of user characteristic data samples. At least one reference gender corresponding to the at least one user characteristic data sample is obtained by querying a preset correspondence between user characteristic data samples and reference genders. Gender of the user is determined according to the at least one reference gender and the gender determined is sent to the mobile terminal.

The present invention provides a system and method for performing an online registration process to obtain registration information and venue information, accessing one or more sources of information about venues, and providing a user interface that includes venue information, a venue map, a location of a user, a location of user's friends on the venue map, and a calendar window for showing various events.

A computer implemented method for analyzing feedback with respect to a virtual assistant includes identifying a technical support problem and a corresponding resolution, wherein the technical support problem corresponds to a query, and wherein the corresponding resolution corresponds to the virtual assistant's response, collecting user feedback provided by one or more users corresponding to the technical support problem and the corresponding resolution, creating a set of user profiles corresponding to the one or more users, generating weighted user feedback according to the set of user profiles, identifying contradictory feedback patterns corresponding to the one or more users, adjusting the set of user profiles according to the identified contradictory feedback patterns, and recommending improvements to the identified corresponding resolution.

Various embodiments provide for the consolidation of policies across multiple identities that are respectively associated with multiple active directory (AD) groups to which a user belongs. Present embodiments provide for dynamically generating a new identity in the resource provider environment that includes permissions to all of the resources that may otherwise be distributed across multiple identities. Specifically, in accordance with various embodiments, when a user login is detected, the active directory is queried to determine the AD groups to which the user belongs. As mentioned, the user's AD groups are mapped to respective identities in the resource provider environment, in which each identity includes policy defining access to one or more resources. The policies of all the respective identities are consolidated and assigned to a new identity. The user may assume the new identity and access all the resources in tandem.

Examples provide a self-supervised language model for document-to-document similarity scoring and ranking long documents of arbitrary length in an absence of similarity labels. In a first stage of a two-staged hierarchical scoring, a sentence similarity matrix is created for each paragraph in the candidate document. A sentence similarity score is calculated based on the sentence similarity matrix. In the second stage, a paragraph similarity matrix is constructed based on aggregated sentence similarity scores associated with the first candidate document. A total similarity score for the document is calculated based on the normalize the paragraph similarity matrix for each candidate document in a collection of documents. The model is trained using a masked language model and intra-and-inter document sampling. The documents are ranked based on the similarity scores for the documents.

An artificial intelligence system includes a first information processing module generating data related to a language based on social data of a first user registered in one or a plurality of social network services, and a second information processing module generating data related to an image based on social data of the first user registered in one or a plurality of social network services. The first information processing module and the second information processing module generate a virtual first user on a computer with respect to the first user.

Systems and methods that can provide verifications and grades corresponding to items represented within ecommerce platforms such as online resume generation, online product marketplace, and online social media platforms. Evaluations of items such as skills, products, users, topics, and characteristics of users and items, contribute to verifications and grades that can be displayed in a user-friendly and understandable manner, employing graphic indicators. Contributions to the verifications and grades can be weighted according to grader profiles and item classification.

A system receives transaction data from payment devices of a user. The system generates a transaction profile of the user based on the received transaction data. Based on the transactional parameters, the system determines a community of the user. The system further receives one or more predefined sub-groups of the community from a database. The one or more sub-groups define subsets of activities, geographic locations, and times. The system identifies one or more rules setting limits on the transactional parameters. Absent receiving additional user interactions, the system generates a suggested community for the user as a function of the one or more rules, the activities, geographic locations, and times of the one or more sub-groups of the community. The system generates a suggested activity to the user based on the suggested community.

Embodiments described herein provide a dense hierarchical retrieval for open-domain question and answering for a corpus of documents using a document-level and passage-level dense retrieval model. Specifically, each document is viewed as a structural collection that has sections, subsections and paragraphs. Each document may be split into short length passages, where a document-level retrieval model and a passage-level retrieval model may be applied to return a smaller set of filtered texts. Top documents may be identified after encoding the question and the documents and determining document relevance scores to the encoded question. Thereafter, a set of top passages are further identified based on encoding of the passages and determining passage relevance scores to the encoded question. The document and passage relevance scores may be used in combination to determine a final retrieval ranking for the documents having the set of top passages.