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公开(公告)号：US12063226B1
公开(公告)日：2024-08-13
申请号：US17484348
申请日：2021-09-24
申请人： Exabeam, Inc.
发明人： Derek Lin , Domingo Mihovilovic , Sylvain Gil
IPC分类号： H04L9/40 , G06F16/901 , H04L41/0631
CPC分类号： H04L63/1416 , G06F16/9024 , H04L41/064 , H04L41/065
摘要： The present disclosure relates to a system, method, and computer program for graph-based multi-stage attack detection in which alerts are displayed in the context of tactics in an attack framework, such as the MITRE ATT&CK framework. The method enables the detection of cybersecurity threats that span multiple users and sessions and provides for the display of threat information in the context of a framework of attack tactics. Alerts spanning an analysis window are grouped into tactic blocks. Each tactic block is associated with an attack tactic and a time window. A graph is created of the tactic blocks, and threat scenarios are identified from independent clusters of directionally connected tactic blocks in the graph. The threat information is presented in the context of a sequence of attack tactics in the attack framework.
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2.发明授权公开(公告)号：US11790388B2
公开(公告)日：2023-10-17
申请号：US17490732
申请日：2021-09-30
申请人： Rakuten Group, Inc.
发明人： Naveed Zanoon , Adam Roth , Feng Xie , Mujtaba Hussain , James Seymour-Lock
IPC分类号： G06Q30/02 , G06Q30/0207 , G06F16/953 , H04W4/30 , G06N3/02 , G06F40/174
CPC分类号： G06Q30/0222 , G06F16/953 , G06F40/174 , G06N3/02 , G06Q30/0239 , H04W4/30
摘要： The present disclosure relates to a system, method, and computer program for automatic coupon code fill in a mobile application. The system identifies a checkout page in a WebView of a mobile application and extracts field data from the checkout page. The system identifies a coupon code field and a cart total field from the field data. The system obtains one or more coupon code(s) and tests the one or more coupon code(s) in the checkout page. The one or more coupon code(s) are tested in the identified coupon code field to determine whether any of the coupon code(s) cause the value associated with the cart total field to decrease. In response to one or more coupon code(s) providing a reward on the checkout page, the system identifies a best coupon code, which it inserts in the identified coupon code field in the checkout page in the mobile application.
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公开(公告)号：US11720951B2
公开(公告)日：2023-08-08
申请号：US17558452
申请日：2021-12-21
申请人： Apttus Corporation
发明人： Kirk G. Krappé
IPC分类号： G06Q30/06 , G06Q30/0601 , H04L51/02 , G06Q30/0207 , H04L67/306
CPC分类号： G06Q30/0633 , G06Q30/0207 , G06Q30/0611 , H04L51/02 , H04L67/306
摘要： The present disclosure relates to an intelligent quote-to-cash software agent (“the Agent”) that enables users to efficiently interface with a quote-to-cash system from external messaging applications. The Agent is able to communicate with users using natural language and to identify quote-to-cash system action requests and associated parameters from natural language communications. The user may communicate with the Agent from one of plurality of messaging applications that are not associated with the quote-to-cash system. In response to identifying a quote-to-cash action request and associated parameters in a communication session with a user, the Agent calls the quote-to-cash system and obtains the applicable quote-to-cash output requested by the user. The Agent forwards the quote-to-cash system output to the user via the external messaging application selected by the user. The Agent may initiate communications with the user to inform the user of an opportunity in the quote-to-cash process.
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公开(公告)号：US11720563B1
公开(公告)日：2023-08-08
申请号：US17991352
申请日：2022-11-21
申请人： Apttus Corporation
IPC分类号： G06F16/24 , G06F16/2453 , G06F16/22
CPC分类号： G06F16/24542 , G06F16/2219 , G06F16/24532 , G06F16/24539
摘要： The present disclosure relates to a large-scale and low-latency data retrieval and storage system for a multi-tenant, cloud-based application, such as a Quote-to-Cash application. Conventionally, such applications rely heavily on SQL databases, which have difficultly providing service and performance at scale. The system of the present disclosure uses a distributed blob storage for data records, wherein each tenant has their own partition within the blob storage. Blob storage is able to provide service and performance at scale. Blob storage alone, however, cannot solve the needs of a multi-tenant, cloud-based application in which customer inputs complex data queries to retrieve data records. The present disclosure describes a system that converts basic blob storage into a data store can manage complex data queries in an efficient and scalable way for multiple tenants. This includes storing queryable data in data structures in a persistent distributed cache and executing queries on the data structures to identify the record IDs that satisfy the query. The records are then retrieved from blob storage using parallel fetch operations.
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公开(公告)号：US11651037B2
公开(公告)日：2023-05-16
申请号：US16869408
申请日：2020-05-07
申请人： Rakuten Group, Inc.
发明人： Yang Shi , Young Joo Chung
IPC分类号： G06F16/903 , G06F40/30 , G06F17/16 , G06F18/22 , G06N3/045 , G06V10/764 , G06V10/774
CPC分类号： G06F16/90348 , G06F17/16 , G06F18/22 , G06F40/30 , G06N3/045 , G06V10/764 , G06V10/774
摘要： The present disclosure relates to a new method for cross-modal retrieval via deep binary hashing and quantization. In a training phase, the system simultaneously learns to generate feature vectors, binary codes, and quantization codes for data across two or more modalities that preserves the semantic similarity correlations in the original data. In a prediction phase, the system retrieve a data item in a database that is semantically similar to a query item of a different modality. To identify the database item closest in semantic meaning to the query item, the system first narrows the database search space based on binary hash code distances between each of the database items and the query item. The system then measures the quantization distances between the query items and the database items in the smaller search space. The system identifies database item have the closest quantization distance to the query item as the closest semantic match to the query item.
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公开(公告)号：US11521639B1
公开(公告)日：2022-12-06
申请号：US17334575
申请日：2021-05-28
申请人： ASAPP, Inc.
发明人： Suwon Shon , Pablo Brusco , Jing Pan , Kyu Jeong Han
摘要： The present disclosure describes a system, method, and computer program for predicting sentiment labels for audio speech utterances using an audio speech sentiment classifier pretrained with pseudo sentiment labels. A speech sentiment classifier for audio speech (“a speech sentiment classifier”) is pretrained in an unsupervised manner by leveraging a pseudo labeler previously trained to predict sentiments for text. Specifically, a text-trained pseudo labeler is used to autogenerate pseudo sentiment labels for the audio speech utterances using transcriptions of the utterances, and the speech sentiment classifier is trained to predict the pseudo sentiment labels given corresponding embeddings of the audio speech utterances. The speech sentiment classifier is then subsequently fine tuned using a sentiment-annotated dataset of audio speech utterances, which may be significantly smaller than the unannotated dataset used in the unsupervised pretraining phase.
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7.发明授权公开(公告)号：US11494644B2
公开(公告)日：2022-11-08
申请号：US16689893
申请日：2019-11-20
申请人： Rakuten, Inc.
摘要： The present disclosure relates to a system, method, and computer program for recommending products using a neural network architecture that directly learns a user's predicted rating for an item from user and item data. A set of encoding neural networks maps each input source for user and item data to a lower-dimensional vector space. The individual lower-dimensional vector outputs of the encoding neural networks are combined to create a single multidimensional vector representation of user and item data. A prediction neural network is trained to predict a user's rating for an item based on the single multidimensional vector representation of user and item data. The neural network architecture allows for more efficient optimization and faster convergence that recommendations systems that rely on autoencoders. The system recommends items to users based on the users' predicted ratings for items.
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公开(公告)号：US11423143B1
公开(公告)日：2022-08-23
申请号：US16228071
申请日：2018-12-20
申请人： Exabeam, Inc.
发明人： Derek Lin , Barry Steiman , Domingo Mihovilovic , Sylvain Gil
摘要： A cybersecurity system, method, and computer program is provided for detecting whether an entity's collection of processes during an interval is abnormal compared to the historical collection of processes observed for the entity during previous intervals of the same length. Logs from a training period are used to calculate global and local risk probabilities for each process based on the process's execution history during the training period. Risk probabilities may be computed using a Bayesian framework. For each entity in a network, an entity risk score is calculated by summing the applicable risk probabilities of the unique processes executed by the entity during an interval. An entity's historical risk scores form a score distribution. If an entity's current score is an outlier on the historical score distribution, an alert of potentially malicious behavior is generated with respect to the entity. Additional post-processing may be performed to reduce false positives.
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公开(公告)号：US11361339B2
公开(公告)日：2022-06-14
申请号：US16919509
申请日：2020-07-02
摘要： The present disclosure relates to a system, method, and computer program for providing users with notifications of a cashback rewards from a shopping portal using screen and email analysis. A shopping portal system analyzes the content and characteristics of user emails, as well as screens viewed by the user through a client application (e.g., webpages and mobile application screens), to identify probable order-confirmation emails and screens. In response to identifying an order-confirmation email or an order-confirmation screen, the system determines whether a cashback reward should be credited to the user for the order corresponding to the order-confirmation email/screen. In response to an order-confirmation email or screen satisfying the criteria for a cashback reward, the system credits a user account with the cashback reward and notifies the user of the reward.
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公开(公告)号：US11232508B2
公开(公告)日：2022-01-25
申请号：US15484594
申请日：2017-04-11
申请人： Apttus Corporation
发明人： Kirk G. Krappé
摘要： The present disclosure relates to an intelligent quote-to-cash software agent (“the Agent”) that enables users to efficiently interface with a quote-to-cash system from external messaging applications. The Agent is able to communicate with users using natural language and to identify quote-to-cash system action requests and associated parameters from natural language communications. The user may communicate with the Agent from one of plurality of messaging applications that are not associated with the quote-to-cash system. In response to identifying a quote-to-cash action request and associated parameters in a communication session with a user, the Agent calls the quote-to-cash system and obtains the applicable quote-to-cash output requested by the user. The Agent forwards the quote-to-cash system output to the user via the external messaging application selected by the user. The Agent may initiate communications with the user to inform the user of an opportunity in the quote-to-cash process.
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