Abstract: One or more computing devices, systems, and/or methods for detecting trigger phrases and transmitting electronic messages to devices are provided. For example, audio received via a microphone of a first device may be monitored. Responsive to detecting a first trigger phrase in a first audio segment identified during the monitoring, a first electronic message comprising instructions to activate a microphone function of a second device may be generated and the first electronic message may be transmitted to the second device. Responsive to detecting a second trigger phrase in a second audio segment identified during the monitoring, a second electronic message comprising instructions to activate a microphone function of a third device may be generated and the second electronic message may be transmitted to the third device.

Abstract: A device, system, and method are directed towards facilitating composing, editing, and displaying a message that includes text and graphics inline. An edit window provides a mechanism for editing the text inline. The message, including text and graphics, may be sent to a remote device. The remote device may display the message, and edit the text and graphics inline, and send a reply message to the original sender.

Abstract: Disclosed are systems and methods for managing online identity authentication risk in a nuanced identity system. For example, a method may include receiving a request by a user for a transaction on an electronic platform; determining a risk associated with the requested transaction; determining a current level of assurance associated with the user on the electronic platform; determining that the risk exceeds the current level of assurance; adjusting the current level of assurance such that the adjusted level of assurance exceeds the risk; and executing the requested transaction on the electronic platform after adjusting the current level of assurance.

Abstract: Systems and methods are disclosed for identifying malicious traffic associated with a website.

Abstract: One or more computing devices, systems, and/or methods for cross-domain action prediction are provided. Action sequence embeddings are generated based upon a textual embedding and a graph embedding utilizing past user action sequences corresponding to sequences of past actions performed by users across a plurality of domains. An autoencoder is trained to utilize the action sequence embeddings to project the action sequence embeddings to obtain intent space vectors. A service switch classifier is trained using the intent space vectors. In response to the service switch classifier predicting that a current user will switch from a current domain to a next domain, the current user is provided with a recommendation of an action corresponding to the next domain.

Abstract: One or more computing devices, systems, and/or methods for generating a list of suggested queries associated with one or more keywords are provided. For example, one or more keywords may be received via a search interface. A plurality of queries associated with the one or more keywords may be determined based upon the one or more keywords and a historical query database. A plurality of relationship scores associated with the plurality of queries may be generated based upon a plurality of search sessions associated with the historical query database. The historical query database may be analyzed to determine a plurality of click rates associated with the plurality of queries. A list of suggested queries may be generated based upon the plurality of relationship scores and the plurality of click rates.

Abstract: The present teaching relates to method, system, medium, and implementations for machine learning. A training sample is first received from a source. A prediction is generated according to the training sample and based on one or more parameters associated with a model. A metric characterizing the prediction is also determined. The prediction and the metric are transmitted to the source to facilitate a determination on whether a ground truth label for the training sample is to be provided. When the ground truth label is received from the source, the one or more parameters of the model are updated based on the prediction and the ground truth label.

Abstract: Methods, programming, and system for modifying a slot value are described herein. In a non-limiting embodiment, an intent may be determined based on a first utterance. A first slot-value pair may be obtained for the first utterance based on the intent, the first slot-value pair including a first slot and a first value associated with the first slot. A second value associated with the first slot may be identified, the second value being identified from a second utterance that was previously received. Based on the intent and the first slot, a type of update to be performed with respect to the second value may be determined. The second value may then be updated based on the first value and the type of update.

Abstract: A method, implemented on at least one computing device each of which has at least one processor, storage, and a communication platform connected to a network for presenting a search result in a search result card, the method includes receiving from a user, an input associated with a search query; fetching one or more search results in accordance with the search query; generating a search result card for each of the one or more search results; and presenting to the user, one or more search result cards as a response to the search query, the one or more search result cards corresponding to the one or more search results, respectively.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content generating, searching, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide systems and methods for privacy-aware machine learning using an improved data encoding that withholds more information. The disclosed systems and methods encode a corpus of data and encode each query used in searching and generating query results from the corpus of encoded data.

Abstract: Systems and methods are disclosed for utilizing sender-recipient pair data to establish sender-level trust in future communication. One method comprises receiving raw communication data over a network and testing the received raw communication data against trained machine learning data to predict whether the raw communication data is associated with expected communication data. The raw communication data is sorted for expected communication data, which is further analyzed for sender-recipient pair data and assigned an expected communication pair data score. Senders associated with an expected communication pair data score that meets or exceeds a threshold are labeled and stored in a database as trusted. As a result of the sender-recipient pair analysis, recipients at-risk for being scammed can be identified, senders misidentified as spammers can be properly classified, and machine learning techniques utilized for analyzing raw communication data can be fine-tuned.

Abstract: One or more computing devices, systems, and/or methods for entity disambiguation are provided. For example, a document may be analyzed to identify a first mention and a second mention. One or more techniques may be used to select and link a candidate entity, from a first set of candidate entities, to the first mention and select and link a candidate entity, from a second set of candidate entities, to the second mention.

Abstract: Disclosed are embodiments for providing batch performance using a stream processor. In one embodiment, a method is disclosed comprising receiving an event, such as a streaming event, from a client. The method determines that the event comprises a primary event and, if so, writes the primary event to a cache and returning the primary event to the client. The method later receives a second event from the client, the second event associated with the first event, annotates the second event based on the primary event, and returns the annotated second event to the client.

Abstract: The present teaching, which includes methods, systems and computer-readable media, relates to providing query suggestions based on a number of data sources that include person's personal data and non-personal data. The disclosed techniques may include receiving an input from a person, obtaining a first set of suggestions based on a person corpus derived from at least one data source private to the person, obtaining a second set of suggestions based on information from an additional data source, ranking the first and second sets of suggestions to generate a ranked list of suggestions, and presenting at least some of the ranked suggestions.

Abstract: A novel framework optimizes SQL queries that are generated from a templated virtual sematic layer. The framework introduces the use of a virtual semantic layer into database management systems' operations, whereby templated SQL queries can be rewritten according to a determined and measured nesting, dimensional structure that produces an optimized search system. This enables templated SQL fragments to be translated for query optimization, thereby reducing the drain on a database's resources and minimizing a query's impact on the database's performance.

Abstract: Disclosed are systems and methods for generating search result data based on machine-encoded text generated by computer vision optical character recognition machine learning techniques performed on digital media. The disclosed systems and methods provide a novel framework for performing machine learning visual search or machine learning text extraction techniques on digital media in order to extract and analyze the data therein and further conduct search queries based on the extracted and analyzed data. The disclosed framework may leverage the aforementioned computer vision machine learning techniques in order to provide a user with relevant search results regarding objects and text detect in digital media captured on a user device.

Abstract: The present teaching relates to method, system, and programming for responding to an image related query. Information related to each of a plurality of images is received, wherein the information represents concepts co-existing in the image. Visual semantics for each of the plurality of images are created based on the information related thereto. Representations of scenes of the plurality of images are obtained via machine learning, based on the visual semantics of the plurality of images, wherein the representations capture concepts associated with the scenes.

Abstract: One or more computing devices, systems, and/or methods are provided. In an example, a first performance metric score may be determined based upon first content item text. A plurality of similarity scores associated with a plurality of sets of content item text may be determined. One or more sets of content item text may be selected from among the plurality of sets of content item text based upon the plurality of similarity scores and a plurality of performance metric scores associated with the plurality of sets of content item text. The plurality of performance metric scores may comprise one or more performance metric scores associated with the one or more sets of content item text. The one or more performance metric scores may be higher than the first performance metric score. One or more representations of the one or more sets of content item text may be displayed.

Abstract: One or more computing devices, systems, and/or methods for implementing a model for serving exploration traffic are provided. An amount of spend by a content provider to provide content items of the content provider through a content serving platform to client devices of users is determined. A number of exploration impressions of users viewing exploration content items of the content provider over a timespan is determined. A return on exploration impression metric is determined for the content provider based upon a ratio of the amount of spend to the number of exploration impressions. The return on exploration metric is used to rank available exploration content items of content providers for serving exploration traffic.

Abstract: Technologies for template generation using directed acyclic word graphs (DAWGs). The technologies can include receiving a first plurality of titles from a first plurality of title feeds, and sorting the first plurality of titles into a plurality of category sets. And, for each category set of the plurality of category sets, the technologies can include transforming the respective titles belonging to the category set into a trie data structure by separating words in the respective titles into nodes of the trie data structure. For each category set, the technologies can also include transforming the trie data structure into a directed acyclic word graph (DAWG) data structure. Also, for each category set, the technologies can also include generating one or more unique templates based on the DAWG data structure.