Abstract: A receiver receives a request to schedule a meeting from a user and in response, prompts the user to provide meeting information including time information and attendee information for scheduling the meeting. A meeting scheduler identifies potential dates and potential times based on the meeting information. The meeting scheduler further detects locations of the attendees based on the potential dates and identifies potential meeting locations based on attendees' location. The meeting scheduler also computes date scores for the potential dates, time scores for the potential times, and location scores for the meeting locations to select a date, a time, and a meeting location based on scores to determine a meeting schedule. The meeting scheduler further selects a conferencing mechanism for the meeting and provides the meeting schedule comprising the selected date, time, and meeting location, and the selected conferencing mechanism as a meeting invite option to the user.

Abstract: A receiver receives a request to schedule a meeting from a user and in response, prompts the user to provide meeting information including time information and attendee information for scheduling the meeting. A meeting scheduler identifies potential dates and potential times based on the meeting information. The meeting scheduler further detects locations of the attendees based on the potential dates and identifies potential meeting locations based on attendees' location. The meeting scheduler also computes date scores for the potential dates, time scores for the potential times, and location scores for the meeting locations to select a date, a time, and a meeting location based on scores to determine a meeting schedule. The meeting scheduler further selects a conferencing mechanism for the meeting and provides the meeting schedule comprising the selected date, time, and meeting location, and the selected conferencing mechanism as a meeting invite option to the user.

Abstract: Systems, methods, and non-transitory computer-readable media can calculate user similarity scores for a plurality of users on a social networking system with respect to a first user based on user embeddings for the plurality of users and the first user. A set of similar users comprising a plurality of similar users is determined based on the user similarity scores. Page recommendation scores are calculated for a plurality of pages associated with the plurality of similar users based on the user similarity scores. One or more page recommendations are determined for the first user based on the page recommendation scores.