Oath Inc.

Michael W Albers

Yoelle Smadja Maarek

Eckart Walther

Liane Lewin-Eytan

Luke Wroblewski

Dotan Di Castro

Zohar Karnin

Rob McCool

Guy Halawi

Systems, methods, and computer program products are disclosed for asking and searching for the answer to given questions, retrieving answers to such questions, as well as presenting such answers in a user-generated content style framework on a search engine. The system of the present invention comprises a question processor, operative to determine whether a question entered by a user has been previously answered, an answer data store storing answers to previously asked questions stored therein, an answer repository storing questions not yet answered by another user, and an editor tool operative to format an answer stored in the answer data store into user-generated content style and migrate the answer to a user-generated content style web page.

System and method for maintenance of questions and answers through collaborative and community editing

As is disclosed herein, user behavior in connection with a number of electronic messages, such as electronic mail (email) messages, can be used to automatically learn from, and predict, whether a message is wanted or unwanted by the user, where an unwanted message is referred to herein as gray spam. A gray spam predictor is personalized for a given user in vertical learning that uses the user's electronic message behavior and horizontal learning that uses other users' message behavior. The gray spam predictor can be used to predict whether a new message for the user is, or is not, gray spam. A confidence in a prediction may be used in determining the disposition of the message, such as and without limitation placing the message in a spam folder, a gray spam folder and/or requesting input from the user regarding the disposition of the message, for example.

Method and apparatus for predicting unwanted electronic messages for a user

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Menlo Park, CA, United States of America

Michael W Albers