Institution
Amazon.com
Company•Seattle, Washington, United States•
About: Amazon.com is a company organization based out in Seattle, Washington, United States. It is known for research contribution in the topics: Service (business) & Service provider. The organization has 13363 authors who have published 17317 publications receiving 266589 citations.
Papers published on a yearly basis
Papers
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24 Sep 2014TL;DR: In this article, the authors describe a system for automatically transitioning items from a materials handling facility without delaying a user as they exit the facility, where the items are identified and associated with the user at or near the time of the item pick.
Abstract: This disclosure describes a system for automatically transitioning items from a materials handling facility without delaying a user as they exit the materials handling facility. For example, while a user is located in a materials handling facility, the user may pick one or more items. The items are identified and automatically associated with the user at or near the time of the item pick. When the users enters and/or passes through a transition area, the picked items are automatically transitioned to the user without affirmative input from or delay to the user.
115 citations
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20 Apr 2018TL;DR: The authors presented a novel approach to learn representations for sentence-level semantic similarity using conversational data, which achieved the best performance among all neural models on the Semantic Textual Similarity (STS) Benchmark and SemEval 2017's Community Question Answering (CQA) question similarity subtask.
Abstract: We present a novel approach to learn representations for sentence-level semantic similarity using conversational data. Our method trains an unsupervised model to predict conversational responses. The resulting sentence embeddings perform well on the Semantic Textual Similarity (STS) Benchmark and SemEval 2017’s Community Question Answering (CQA) question similarity subtask. Performance is further improved by introducing multitask training, combining conversational response prediction and natural language inference. Extensive experiments show the proposed model achieves the best performance among all neural models on the STS Benchmark and is competitive with the state-of-the-art feature engineered and mixed systems for both tasks.
115 citations
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11 Dec 2015TL;DR: In this paper, a speech-based system includes an audio device in a user premises and a network-based service that supports use of the audio device by multiple applications, such as music, audio books, etc.
Abstract: A speech-based system includes an audio device in a user premises and a network-based service that supports use of the audio device by multiple applications. The audio device may be directed to play audio content such as music, audio books, etc. The audio device may also be directed to interact with a user through speech. The network-based service monitors event messages received from the audio device to determine which of the multiple applications currently has speech focus. When receiving speech from a user, the service first offers the corresponding meaning to the application, if any, that currently has primary speech focus. If there is no application that currently has primary speech focus, or if the application having primary speech focus is not able to respond to the meaning, the service then offers the user meaning to the application that currently has secondary speech focus.
115 citations
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TL;DR: It is interesting to explore the fact that hypoxia survivorship increases due to combining effects of suppressing metabolic rates and increasing anaerobic power as fish grow, and this is the first description of scaling effects on Hypoxia tolerance.
Abstract: Astronotus ocellatus is one of the most hypoxia tolerant fish of the Amazon; adult animals can tolerate up to 6 h of anoxia at 28°C. Changes in energy metabolism during growth have been reported in many fish species and may reflect the way organisms deal with environmental constraints. We have analyzed enzyme levels (lactate dehydrogenase, LDH: EC 1.1.1.27; and malate dehydrogenase, MDH: EC 1.1.1.37) in four different tissues (white muscle, heart, liver, and brain) from different-sized animals. Both enzymes correlate with body size, increasing the anaerobic potential positively with growth. To our knowledge, this is the first description of scaling effects on hypoxia tolerance and it is interesting to explore the fact that hypoxia survivorship increases due to combining effects of suppressing metabolic rates and increasing anaerobic power as fish grow.
114 citations
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30 Sep 2010TL;DR: In this paper, the authors proposed a method for providing information to a user of a mobile device based on an online or web-identity of the user and a geolocation of the mobile device.
Abstract: Techniques for providing information to a user of a mobile device based on an online or web-identity of the user and a geolocation of the mobile device are described herein. The user may be notified when a nearby merchant has a good or service for sale that matches a good or service in a list, such as a wish list, associated with the web-identity of the user. The users may also be provided access to a coupon within an electronic document when a mobile device storing the electronic document is located at a particular merchant. This convergence of geographical location of the user, as determined by the geolocation of his or her mobile device, with his or her web-identity can bring the online and off-line worlds closer together to provide relevant information for the user and improved marketing opportunities for merchants.
114 citations
Authors
Showing all 13498 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jiawei Han | 168 | 1233 | 143427 |
Bernhard Schölkopf | 148 | 1092 | 149492 |
Christos Faloutsos | 127 | 789 | 77746 |
Alexander J. Smola | 122 | 434 | 110222 |
Rama Chellappa | 120 | 1031 | 62865 |
William F. Laurance | 118 | 470 | 56464 |
Andrew McCallum | 113 | 472 | 78240 |
Michael J. Black | 112 | 429 | 51810 |
David Heckerman | 109 | 483 | 62668 |
Larry S. Davis | 107 | 693 | 49714 |
Chris M. Wood | 102 | 795 | 43076 |
Pietro Perona | 102 | 414 | 94870 |
Guido W. Imbens | 97 | 352 | 64430 |
W. Bruce Croft | 97 | 426 | 39918 |
Chunhua Shen | 93 | 681 | 37468 |