Visa Inc.

About: Visa Inc. is a company organization based out in London, United Kingdom. It is known for research contribution in the topics: Database transaction & Transaction data. The organization has 1031 authors who have published 1076 publications receiving 36053 citations. The organization is also known as: Visa & Visa Inc.

System and method for online analysis

Abstract: A method is disclosed. The method includes receiving, from a user computer that is a party to a transaction, information that can be used to identify a transaction between the user computer and a resource provider computer. The method further includes determining one or more attributes. The method additionally includes presenting a first question based on the one or more attributes. The method also includes receiving a response to the first question, presenting a second question based on the received response, and receiving a response to the second question. The method further includes storing the received responses in a data storage element, wherein the data storage element is accessible by an authorizing entity computer.

Systems and methods to organize data supporting efficient processing of large scale propagation of resources among users of accounts

Abstract: Accounts are grouped in a database via replaceable connections and non-replaceable connections to form account groups that can be used to efficiently track the propagation of resources or privileges among users. Accounts that can be treated as a same account are linked or grouped via replaceable connections. Accounts having different ownerships are grouped via non-replaceable connections. The account groups created via the replaceable connections and non-replaceable connections can be used to track offer sharing and/or distribution from primary accounts to secondary accounts in respective account groups. For example, users of an offer propagation platform may split an offer into sub-offers and share sub-offers with others. Using replaceable and non-replaceable account groups the system can operate with the capability of supporting linked accounts in millions, allowing the offers to be propagated among users via sharing, redistribution and/or subdivision for improved usage.

Stock Price Prediction using Bidirectional LSTM with Attention

Abstract: The stock market is one of the most important topics of today’s economy due to its fluctuating nature and far-reaching impact. Despite the difficulty of mathematical modeling of time-series of stock prices, deep learning and black-box modeling have been reported to perform well in literature. In this work, we have experimented with different recurrent neural network architectures to predict stock prices for elite Nasdaq companies. We have improved the baseline models by reducing the number of parameters and using bidirectional processing with attention. We show that using a Gaussian noise vector can regularize the model to improve the robustness without using any dropout. Our proposed model achieves the lowest mean square error for AMZN (0.12), AAPL (0.15), NFLX (0.03), GOOG (0.08), GOOGL (0.06), CSCO (0.01), COST (0.06), FB (0.03), 8 out of 10 companies. Our work aims to show that with better architecture design, RNN variants can outperform baseline models despite having a fraction of the parameters.

System and method for detecting network topology

Abstract: Described herein are systems, methods, apparatuses, and computer readable media for generating a network topology for a network based on dependencies between network components. Transactions between network components may be monitored in accordance with at least some embodiments. Dependencies may be identified between network applications and/or network devices based on detected transactions detected between those network components. A network topology may then be generated for a network based on the identified dependencies. In some embodiments, the network topology may be used to determine an impact score for one or more network components within the network. An impact score may be used to make determinations with respect to the network.

Systems and methods for protecting against relay attacks

Abstract: Systems, methods, and devices are disclosed for preventing relay attacks. A user device may receive (e.g., when proximate to the first access device), from an intervening device, device identification data for a first access device. A message may be received from a second access device via the intervening device. The message may include a digital signature generated based at least in part on second access device identification data. The user device may validate the message utilizing the digital signature and a public key. If the message is invalid, the user device may discard the message. If the message is valid, (e.g., unaltered), the user device may determine that the user has not confirmed an intent to interact with the second access device and may terminate an further interaction with the second access device accordingly.