Abstract: An online system using attributes of users to select content for presentation to the users predicts one or more attributes of users whose attributes are unavailable to the online system. For a user with one or more attributes unavailable to the online system, the online system applies a model to attributes of additional users to predict one or more attributes of the user. Attributes of the additional user use in the prediction may include demographic information and interactions with content by the additional users. The online system may determine an accuracy of the model by using the model to predict attributes for users whose attributes are known to the online system and comparing the predicted attributes to the known attributes. If the model's accuracy is less than a threshold value, the online system discontinues using the model to predict attributes of users.

Abstract: An online system using attributes of users to select content for presentation to the users predicts one or more attributes of users whose attributes are unavailable to the online system. For a user with one or more attributes unavailable to the online system, the online system applies a model to attributes of additional users to predict one or more attributes of the user. Attributes of the additional user use in the prediction may include demographic information and interactions with content by the additional users. The online system may determine an accuracy of the model by using the model to predict attributes for users whose attributes are known to the online system and comparing the predicted attributes to the known attributes. If the model's accuracy is less than a threshold value, the online system discontinues using the model to predict attributes of users.

Abstract: An online system using attributes of users to select content for presentation to the users predicts one or more attributes of users whose attributes are unavailable to the online system. For a user with one or more attributes unavailable to the online system, the online system applies a model to attributes of additional users to predict one or more attributes of the user. Attributes of the additional user use in the prediction may include demographic information and interactions with content by the additional users. The online system may determine an accuracy of the model by using the model to predict attributes for users whose attributes are known to the online system and comparing the predicted attributes to the known attributes. If the model's accuracy is less than a threshold value, the online system discontinues using the model to predict attributes of users.

Abstract: An online system maintains topic vectors associated with various content items, where a vector associated with a content item indicates a topic vector of a content item. Words in a content item and context traits describing presentation of the words in the content item are used by the online system to determine a topic vector associated with the content item. When a subject content item for display, the online system determines the topic vector associated with the subject content item and identifies topic vectors associated with other content items nearest to the topic vector associated with the subject content item in a vector space through application of one or more clustering algorithms to the topic vectors. Content items associated with the identified topic vectors are indicated as similar to the subject content item by the online system.