Abstract: Computerized systems and methods are disclosed for performing contextual classification of objects using supervised and unsupervised training. In accordance with one implementation, content reviewers may review training objects and submit supervised training data for preprocessing and analysis. The supervised training data may be preprocessed to identify key terms and phrases, such as by stemming, tokenization, or n-gram analysis, and form vectorized objects. The vectorized objects may be used to train one or more models for subsequent classification of objects. In certain implementations, preprocessing or training, among other steps, may be performed in parallel over multiple machines to improve efficiency. The disclosed systems and methods may be used in a wide variety of applications, such as article classification and content moderation.

Abstract: Computerized systems and methods are disclosed for performing contextual classification of objects using supervised and unsupervised training. In accordance with one implementation, content reviewers may review training objects and submit supervised training data for preprocessing and analysis. The supervised training data may be preprocessed to identify key terms and phrases, such as by stemming, tokenization, or n-gram analysis, and form vectorized objects. The vectorized objects may be used to train one or more models for subsequent classification of objects. In certain implementations, preprocessing or training, among other steps, may be performed in parallel over multiple machines to improve efficiency. The disclosed systems and methods may be used in a wide variety of applications, such as article classification and content moderation.

Abstract: Systems and methods are disclosed for online distribution of content based on a user sentiment index. The method may include receiving, over a network and from a user device, one or more user generated inputs and calculating the user sentiment index based on the one or more user generated inputs. The method may also include receiving, over the network, from a content or advertising provider, instructions on publishing content or advertising to a webpage based on the calculated user sentiment index, and publishing content for display on user devices over the network based on a comparison of the calculated user sentiment index and the received instructions.

Abstract: Systems and methods are disclosed for online distribution of content based on a user sentiment index. The method may include receiving, over a network and from a user device, one or more user generated inputs and calculating the user sentiment index based on the one or more user generated inputs. The method may also include receiving, over the network, from a content or advertising provider, instructions on publishing content or advertising to a webpage based on the calculated user sentiment index, and publishing content for display on user devices over the network based on a comparison of the calculated user sentiment index and the received instructions.

Abstract: Systems and methods are disclosed for online distribution of content based on a user sentiment index. The method may include receiving, over a network and from a user device, one or more user generated inputs and calculating the user sentiment index based on the one or more user generated inputs. The method may also include receiving, over the network, from a content or advertising provider, instructions on publishing content or advertising to a webpage based on the calculated user sentiment index, and publishing content for display on user devices over the network based on a comparison of the calculated user sentiment index and the received instructions.

Abstract: Systems and methods are disclosed for online distribution of content based on a user sentiment index. The method may include receiving, over a network and from a user device, one or more user generated inputs and calculating the user sentiment index based on the one or more user generated inputs. The method may also include receiving, over the network, from a content or advertising provider, instructions on publishing content or advertising to a webpage based on the calculated user sentiment index, and publishing content for display on user devices over the network based on a comparison of the calculated user sentiment index and the received instructions.

Abstract: Computerized systems and methods are disclosed for performing contextual classification of objects using supervised and unsupervised training. In accordance with one implementation, content reviewers may review training objects and submit supervised training data for preprocessing and analysis. The supervised training data may be preprocessed to identify key terms and phrases, such as by stemming, tokenization, or n-gram analysis, and form vectorized objects. The vectorized objects may be used to train one or more models for subsequent classification of objects. In certain implementations, preprocessing or training, among other steps, may be performed in parallel over multiple machines to improve efficiency. The disclosed systems and methods may be used in a wide variety of applications, such as article classification and content moderation.

Abstract: Techniques are provided for controlling access to an application. A first request to use an application may be received from a first user and an application access rule associated with the first user may be accessed. Based on the application access rule, it may be determined that permission is required for the first user to use the application. In response, a second request may be sent to a second user requesting permission for the first user to use the application and a response to the second request may be received from the second user. The response may include authorization information used in determining whether the first user has permission from the second user to use the application. In response to receiving the response from the second user, the first request to use the application initiated by the first user may be handled based on the authorization information.

Abstract: Systems and methods are disclosed for online distribution of content based on a user sentiment index. The method may include receiving, over a network and from a user device, one or more user generated inputs and calculating the user sentiment index based on the one or more user generated inputs. The method may also include receiving, over the network, from a content or advertising provider, instructions on publishing content or advertising to a webpage based on the calculated user sentiment index, and publishing content for display on user devices over the network based on a comparison of the calculated user sentiment index and the received instructions.

Abstract: Methods, computer-readable media, and systems are provided to facilitate a second user to allow or deny a first user, such as a child, from accessing content by proving the second user with a content profile based on decisions made by other users with respect to the content. In one implementation, a system allows the second user to set a threshold to automatically allow or deny access based on the other users' decisions. The decisions made by other users are aggregated into information that may be based on similarities between the child and other children from whom other users have previously made decisions regarding the particular content. In addition, the aggregation may more heavily weight decisions by users that have a history of making similar decisions to the second user.

Abstract: Methods, computer-readable media, and systems are provided to facilitate a second user to allow or deny a first user, such as a child, from accessing content by proving the second user with a content profile based on decisions made by other users with respect to the content. In one implementation, a system allows the second user to set a threshold to automatically allow or deny access based on the other users' decisions. The decisions made by other users are aggregated into information that may be based on similarities between the child and other children from whom other users have previously made decisions regarding the particular content. In addition, the aggregation may more heavily weight decisions by users that have a history of making similar decisions to the second user.

Abstract: Methods, computer-readable media, and systems are provided to facilitate a second user to allow or deny a first user, such as a child, from accessing content by proving the second user with a content profile based on decisions made by other users with respect to the content. In one implementation, a system allows the second user to set a threshold to automatically allow or deny access based on the other users' decisions. The decisions made by other users are aggregated into information that may be based on similarities between the child and other children from whom other users have previously made decisions regarding the particular content. In addition, the aggregation may more heavily weight decisions by users that have a history of making similar decisions to the second user.

Abstract: The disclosed hybrid architecture provides secure peer-to-peer communication between devices such as computers, wireless devices, personal digital assistants (PDAs), web enabled phones or the like. This architecture includes a server or Peer Switch, which acts as an intermediary to facilitate the session and provide authentication to ensure system security. In some cases it may also provide the capability necessary to traverse firewalls and deal with proxies and other obstacles to peer-to-peer communications. The hybrid architecture allows centralized administration and policy management of authentication, obstacle transversal and security methods, to ensure the overall system integrity required by business systems. Typical peer user devices implement peer client programming, for signaling communication with the server and for peer-to-peer communications with other peer devices. A web server may also provide access via standard browsers, for users having devices lacking the peer client software.