Yahoo Assets LLC

Amazon Technologies, Inc.

Microsoft Technology Licensing, LLC

Verizon Media Inc.

Oath Inc.

Excalibur IP, LLC

Iftah Gamzu

Liane Lewin-Eytan

Irena Grabovitch-Zuyev

Noa Avigdor-Elgrabli

Yoelle Smadja Maarek

Natalia Silberstein

Dotan Di Castro

Abhinav Pundir

Xiaoxin Yin

Joseph Yossi Azar

Yochai Zvik

Nissim Halabi

Marina Haikin

Oren Shlomo Somekh

Zohar Karnin

Ran Levy

Keren Baruch

David Wajc

Natali Arieli

Ian McCarthy

Sagi Bernstein

Yehuda Finkelstein

Haim Litvak

Christopher Royer

Moshe Peretz

Yossi Shasha

Disclosed are systems and methods for improving interactions with and between computers in electronic messaging, and other, 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 automatically generating data extraction rules, which can then be used to automatically extract data from electronic messages.

Automatic electronic message content extraction method and apparatus

Devices and techniques are generally described for adaptive targeting for voice notifications. In various examples, first data representing a predicted likelihood that a first user will interact with first content within a predefined amount of time may be received. A first set of features including features related to past voice notifications sent to the first user may be determined. A second set of features including features related to interaction with the first content when past voice notifications were sent may be received. A first machine learning model may generate a prediction that a voice notification will increase a probability that the first user interacts with the first content based on the first data, the first set of features, and the second set of features. Audio data comprising the voice notification may be sent to a first device associated with the first content.

Adaptive targeting for proactive voice notifications

Disclosed are systems and methods for improving interactions with and between computers in content searching, hosting and/or providing systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods for efficiently monitoring and following up on delivered messages for which a user expects and/or requires a reply. The disclosed functionality provides a fully automated, personalized, easy and efficient way to identify and manage outgoing mail messages that require reply by marking outbound messages as RSVP messages, which are those messages determined to require a reply. Such functionality is based on the ability of the disclosed framework to distinguish between a 'satisfactory response' (i.e., a response that includes the required information) and a response that is not.

Computerized system and method for controlling electronic messages and their responses after delivery

Systems and methods are described for mitigating errors introduced during processing of user input such as voice input. A query may be derived from processed user input. A performance predictor analyzes the query and uses historical data to predict whether the query will return relevant results if executed. If the query's predicted performance is below a threshold, a query rewriter may identify potential alternatives to the query from a library of 'known good' queries. Different analyzers may be applied to identify different sets of alternatives, and machine learning models may be applied to rank the outputs of the analyzers. The best-matching alternatives from each analyzer may then be provided as inputs to a further machine learning model, which assesses the probability that each of the identified alternatives reflects the intent of the user. A most likely alternative may then be selected to execute in place of the original query.

Rewriting queries

The present teaching relates to providing a recommendation for subscribing to or unsubscribing from an electronic communication. In one example, actions of a user are obtained with respect to electronic communications of the user. One or more categories of the electronic communications are determined. A state of the user is determined based on the actions and the one or more categories. The state is either a discovery state indicating that the user expresses an interest to receive electronic communications associated with a specific category or a cleaning state indicating that the user lacks an interest in one or more received electronic communications. A subscribe recommendation for subscribing to electronic communications associated with the specific category is provided when the state is determined to be a discovery state. An unsubscribe recommendation for unsubscribing from electronic communications similar to the one or more received electronic communications is provided when the state is determined to be a cleaning state.

Method and system for providing subscribe and unsubscribe recommendations

Systems and methods are described herein for generating adaptive feedback in response to a user request. Input indicative of a user request may be received and utilized to identify an item in an electronic catalog. A title for the item may be retrieved and provided, as input, to a machine-learning model. The machine-learning model may be trained to identify one or more segments of an input title. A shortened title may be generated from these identified segments and provided as output at the user device (e.g., via audible output provided at a speaker of the user device). In some embodiments, the length and content of the shortened title may vary based at least in part on the contextual intent of the user's request.

Techniques to provide adaptive feedback

Disclosed is a system, method, and non-transitory computer readable storage medium for predicting future messages. A processor receives a message sent to a user operating a client device, analyzes the message in light of previously identified patterns and scores assigned to scanned messages, determines a future message that should be received by the client device based on the received message, and transmits an item of information based on the determined future message.

Method and system for predicting future email

Techniques and systems are disclosed providing improved ranking of results to an online search-based query. One or more user types are identified for a search-based query, and may correspond to a number of user relevant results, and which user results are selected. A user profile can be determined for the respective user types for the search-based query, which may identify a proportion of the users that belong to that type, and how many results are relevant to that type. A set of relevant results can be identified for the respective user types for the search-based query, based on a number of results used by the user type. An improved ranking of the results can be determined for the search-based query, from the one or more sets of relevant results, based on user profiles and a desired user satisfaction metric for a desired number of users.

Ranking results of multiple intent queries

Techniques and systems are disclosed providing improved ranking of results to an online search-based query. One or more user types are identified for a search-based query, which may correspond to a number of user relevant results and which ones are selected. A user profile can be determined for the respective user types for the search-based query, which may identify a proportion of the users that belong to that type, and how many results are relevant to that type. A set of relevant results can be identified for the respective user types for the query, based on a number of results used by the user type. An improved ranking of the results can be determined for the query, from the one or more sets of relevant results, based on the user profiles and a desired user satisfaction metric for a desired number of users.

Growing community of inventors

Rishon Lezion, Israel

Iftah Gamzu