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公开(公告)号:US11100544B1
公开(公告)日:2021-08-24
申请号:US14980556
申请日:2015-12-28
Applicant: Amazon Technologies, Inc.
Inventor: Adam James Finkelstein , Ho Nam Ho , Markus Wai-Keen Kwok , Siqi Zhao
IPC: G06Q30/02 , G06K9/62 , G06K9/46 , G06F16/51 , G06F16/583
Abstract: A service may create image-based reviews, which include minimal or no text, to assist customers in researching products. The reviews may include images sorted or grouped (e.g., by sentiment, by product review rating, by age of item, by number of uses, etc.). Images of items may be obtained by the service from user reviews and/or other sources. The images may be associated with text, such as at least some text from associated reviews, commentary, and/or other metadata. The images may be analyzed by a classifier to identify features in the visual image, such as a location of a particular item. The images may be categorized for use in one or more user interfaces that provide image-based item reviews. In some embodiments, the images may be arranged based on a number of uses of the item in the image or by an item age of the item in the image.
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公开(公告)号:US10742716B1
公开(公告)日:2020-08-11
申请号:US14108256
申请日:2013-12-16
Applicant: Amazon Technologies, Inc.
Inventor: Adam James Finkelstein , David Akira Gingrich
Abstract: A digital media service distributes digital media content to a plurality of devices in a graphical processing unit based distributed cluster and transmits executable instructions to these devices to initiate a collaborative filtering algorithm. Accordingly, the graphical processing unit in each of the devices, configured to utilize the collaborative filtering algorithm, may generate one or more co-occurrence vectors comprising similarities among a user's interactions with the digital media content and other users' interactions with the digital media content. These co-occurrence vectors are transmitted to the digital media service, which may create a matrix based at least in part on these vectors to determine personalized digital media content that is to be distributed to each of the devices in the distributed cluster. Accordingly, the personalized digital media content is distributed to each device in the distributed cluster.
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公开(公告)号:US09798960B2
公开(公告)日:2017-10-24
申请号:US15414433
申请日:2017-01-24
Applicant: Amazon Technologies, Inc.
Inventor: Anthony Alexander Santos , Adam James Finkelstein , David Akira Gingrich , David Michael Hurley , Siqi Zhao
CPC classification number: G06K9/66 , G06F17/30247 , G06F17/30256 , G06F17/3028 , G06K9/46 , G06K9/4628 , G06K9/6202 , G06K9/623 , G06K9/6282 , G06N3/04 , G06N3/0427 , G06N3/0454 , G06N3/08
Abstract: A system that identifies attributes of an item depicted in an image using artificial intelligence is provided. For example, the system may use one or more deep belief networks (DBNs) or convolution neural networks (CNNs) trained to analyze images and identify attributes in items depicted in the images. A first artificial intelligence module may analyze an image to determine a type of item depicted in the image. The system may then select a second artificial intelligence module that is associated with the type of item and use the second artificial intelligence module to identify attributes in the item depicted in the image. Identified attributes, if associated with a confidence level over a threshold value, may be provided to a user. The user may provide feedback on the accuracy of the identified attributes, which can be used to further train the first and/or second artificial intelligence modules.
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公开(公告)号:US09569700B1
公开(公告)日:2017-02-14
申请号:US14573892
申请日:2014-12-17
Applicant: Amazon Technologies, Inc.
Inventor: Anthony Alexander Santos , Adam James Finkelstein , David Akira Gingrich , David Michael Hurley , Siqi Zhao
CPC classification number: G06K9/66 , G06F17/30247 , G06F17/30256 , G06F17/3028 , G06K9/46 , G06K9/4628 , G06K9/6202 , G06K9/623 , G06K9/6282 , G06N3/04 , G06N3/0427 , G06N3/0454 , G06N3/08
Abstract: A system that identifies attributes of an item depicted in an image using artificial intelligence is provided. For example, the system may use one or more deep belief networks (DBNs) or convolution neural networks (CNNs) trained to analyze images and identify attributes in items depicted in the images. A first artificial intelligence module may analyze an image to determine a type of item depicted in the image. The system may then select a second artificial intelligence module that is associated with the type of item and use the second artificial intelligence module to identify attributes in the item depicted in the image. Identified attributes, if associated with a confidence level over a threshold value, may be provided to a user. The user may provide feedback on the accuracy of the identified attributes, which can be used to further train the first and/or second artificial intelligence modules.
Abstract translation: 提供了一种使用人工智能识别图像中描绘的项目的属性的系统。 例如,该系统可以使用经过训练的一个或多个深层信念网络(DBN)或卷积神经网络(CNN)来分析图像并识别图像中描绘的项目的属性。 第一人造智能模块可以分析图像以确定图像中描绘的项目的类型。 系统然后可以选择与项目类型相关联的第二人造智能模块,并使用第二人造智能模块来识别图像中描绘的项目中的属性。 如果与置信水平超过阈值相关联的标识属性可以被提供给用户。 用户可以提供关于所识别的属性的准确性的反馈,其可以用于进一步训练第一和/或第二人工智能模块。
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公开(公告)号:US10410273B1
公开(公告)日:2019-09-10
申请号:US14562451
申请日:2014-12-05
Applicant: Amazon Technologies, Inc.
Inventor: Adam James Finkelstein , David Akira Gingrich , David Michael Hurley , Stephen Brent Ivie , Siu Nam Wong , Siqi Zhao
Abstract: A recommendation system uses artificial intelligence to identify, based on negative sentiment cues from users, item attributes, such as keywords, that users may find offensive or undesirable. The negative sentiment cues may be explicit (e.g., a user selects an option not to view a particular recommendation again), implicit (e.g., a user does not interact with recommendations relating to an attribute), or both. The system may use a computer model generated based on these identified attributes to filter or modify recommendations to a user or group of users. For instance, if a particular keyword is identified as highly offensive to a group of users, items associated with the keyword may be filtered from item recommendations presented to the group of users. If an attribute is identified as moderately offensive to a user, items associated with the attribute may be down-weighted in item recommendations presented to the user.
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公开(公告)号:US10410125B1
公开(公告)日:2019-09-10
申请号:US14562567
申请日:2014-12-05
Applicant: Amazon Technologies, Inc.
Inventor: Adam James Finkelstein , David Akira Gingrich , David Michael Hurley , Stephen Brent Ivie , Siu Nam Wong , Siqi Zhao
Abstract: A recommendation system uses artificial intelligence to identify, based on negative sentiment cues from users, item attributes, such as keywords, that users may find offensive or undesirable. The negative sentiment cues may be explicit (e.g., a user selects an option not to view a particular recommendation again), implicit (e.g., a user does not interact with recommendations relating to an attribute), or both. The system may use a computer model generated based on these identified attributes to filter or modify recommendations to a user or group of users. For instance, if a particular keyword is identified as highly offensive to a group of users, items associated with the keyword may be filtered from item recommendations presented to the group of users. If an attribute is identified as moderately offensive to a user, items associated with the attribute may be down-weighted in item recommendations presented to the user.
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公开(公告)号:US11941680B1
公开(公告)日:2024-03-26
申请号:US16551537
申请日:2019-08-26
Applicant: Amazon Technologies, Inc.
Inventor: Stephen Brent Ivie , Ashutosh Vishwas Kulkarni , Saurabh Nangia , Adam Landry Bordelon , Aaron James Dykstra , David Michael Hurley , Adam James Finkelstein , Scott James McKee
IPC: G06Q30/0601 , G06Q30/06 , H04L9/40
CPC classification number: G06Q30/0631 , G06Q30/06 , G06Q30/0641 , H04L63/08
Abstract: Social network postings, including text, images or other media, may provide valuable information regarding a user of the social network with which the postings may be associated. With the authorization of the user, and upon authentication by the social network, an online marketplace may access the social network postings and extract data therefrom, and market one or more recommended items to the user based on the extracted data, which may include color pallets or texture pallets derived from photographs included in the postings.
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公开(公告)号:US10395297B1
公开(公告)日:2019-08-27
申请号:US13675333
申请日:2012-11-13
Applicant: Amazon Technologies, Inc.
Inventor: Stephen Brent Ivie , Ashutosh Vishwas Kulkarni , Saurabh Nangia , Adam Landry Bordelon , Aaron James Dykstra , David Michael Hurley , Adam James Finkelstein , Scott James McKee
Abstract: Social network postings, including text, images or other media, may provide valuable information regarding a user of the social network with which the postings may be associated. With the authorization of the user, and upon authentication by the social network, an online marketplace may access the social network postings and extract data therefrom, and market one or more recommended items to the user based on the extracted data, which may include color pallets or texture pallets derived from photographs included in the postings.
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公开(公告)号:US09818145B1
公开(公告)日:2017-11-14
申请号:US13906744
申请日:2013-05-31
Applicant: Amazon Technologies, Inc.
Inventor: Adam James Finkelstein , Adam Edward Shirey , Phivos Costas Avistides
CPC classification number: G06Q30/0631
Abstract: Recommendations of items may be provided to a customer who purchases items from an online marketplace on behalf of a user account based on the interactions of the customer with the marketplace or with one or more external resources, such as a social network account affiliated with the customer. For example, systems and methods may utilize such interactions to determine which of the purchases of items on behalf of the user account are affiliated with the customer, and which may be affiliated with one or more other individuals. Similarly, the systems and methods may also identify recommendations for customers who have purchased items for delivery to a destination based on other items that have been delivered to the destination, and may further determine when a customer has purchased an item for a recipient who has already received the item from another customer.
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公开(公告)号:US20170132497A1
公开(公告)日:2017-05-11
申请号:US15414433
申请日:2017-01-24
Applicant: Amazon Technologies, Inc.
Inventor: Anthony Alexander Santos , Adam James Finkelstein , David Akira Gingrich , David Michael Hurley , Siqi Zhao
CPC classification number: G06K9/66 , G06F17/30247 , G06F17/30256 , G06F17/3028 , G06K9/46 , G06K9/4628 , G06K9/6202 , G06K9/623 , G06K9/6282 , G06N3/04 , G06N3/0427 , G06N3/0454 , G06N3/08
Abstract: A system that identifies attributes of an item depicted in an image using artificial intelligence is provided. For example, the system may use one or more deep belief networks (DBNs) or convolution neural networks (CNNs) trained to analyze images and identify attributes in items depicted in the images. A first artificial intelligence module may analyze an image to determine a type of item depicted in the image. The system may then select a second artificial intelligence module that is associated with the type of item and use the second artificial intelligence module to identify attributes in the item depicted in the image. Identified attributes, if associated with a confidence level over a threshold value, may be provided to a user. The user may provide feedback on the accuracy of the identified attributes, which can be used to further train the first and/or second artificial intelligence modules.
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