Mike Bidgoli

Disclosed are systems and methods for presenting supplemental content items on a user device while requested additional content is obtained. For example, a user is presented with a content item, such as an image, an advertisement, etc., on a display of a user device. The content item, when interacted with by the user, results in a request for additional content, such as a web page, being sent to a remote computing resource, the additional content item being received by the user device from the… Show more

Disclosed are systems and methods for presenting supplemental content items on a user device while requested additional content is obtained. For example, a user is presented with a content item, such as an image, an advertisement, etc., on a display of a user device. The content item, when interacted with by the user, results in a request for additional content, such as a web page, being sent to a remote computing resource, the additional content item being received by the user device from the remote computing resource, loaded by the user device, and presented to the user on the display of the user device. Rather than presenting the user with a blank screen, an empty window, a “loading” notification (e.g., spinning icon), etc., while the additional content item is retrieved and loaded, the implementations discussed herein provide the user with effectively instant gratification by presenting on the display of the user device and while the additional content item is retrieved and loaded, supplemental content that is already stored in memory of the user device. Show less

The present disclosure describes a deal engine that provides merchants with the ability to generate custom deals targeted to particular customers. These custom deals may be generated based on information about, for example, the merchant, the type of targeted customer, and/or historical information about the types of deals to be offered.

In general, one aspect of the subject matter described in this specification may include the actions of receiving, at a server and from a client device… Show more

The present disclosure describes a deal engine that provides merchants with the ability to generate custom deals targeted to particular customers. These custom deals may be generated based on information about, for example, the merchant, the type of targeted customer, and/or historical information about the types of deals to be offered.

In general, one aspect of the subject matter described in this specification may include the actions of receiving, at a server and from a client device of a merchant, a request for a deal, the request including a merchant identifier. The actions then include accessing, at the server, merchant information based on the merchant identifier, the merchant information including a merchant category and a merchant location. Then the actions include obtaining, at the server, a set of candidate deals based on the merchant category and the merchant location. For each candidate deal, the actions include obtaining, at the server, historical information on the respective candidate deal, the historical information corresponding to one or more conversion rates of the candidate deal when the candidate deal was previously offered by one or more merchants and, determining, at the server, a predicted conversion rate based on the historical information for the respective candidate deal. The actions then include selecting, at the server, a deal based on the predicted conversion rates for the set of candidate deals. Finally, the actions include communicating, from the server, data corresponding to the selected deal to the client device, the data including the predicted conversion rate for the selected deal. Show less

A computer implemented method for filtering unwanted bulk email in an email system and providing a positive user experience is provided. The method enables protection of email users from unsolicited bulk email using user-provided data on user interactions at both a user storage level and a global level with an email system. Metadata on user interactions with messages is collected. Messages are received by the system and evaluated using a global filter which assigns a score resulting in a… Show more

A computer implemented method for filtering unwanted bulk email in an email system and providing a positive user experience is provided. The method enables protection of email users from unsolicited bulk email using user-provided data on user interactions at both a user storage level and a global level with an email system. Metadata on user interactions with messages is collected. Messages are received by the system and evaluated using a global filter which assigns a score resulting in a message action. The action may be message delivery, message non-delivery or message routing, based on a score assigned by the global filter. When the message is delivered to user storage, the message may be examined relative to the metadata, and may alter the message action to an action different than the message action resulting from the score. Metadata for a plurality of users is returned to the global filter for use in making filtering future messages and modifies the global filter. Show less

A computer implemented system and method to enable protection of email users from unsolicited bulk email using a message delivery delay based on characteristics detected in selected messages. Messages are evaluated for characteristics resembling unsolicited bulk email. A determination is made whether a message passing through the email system exhibits such characteristics and whether to delay the message. Suspect messages may be delayed for a period of time, the delay period being dependent on… Show more

A computer implemented system and method to enable protection of email users from unsolicited bulk email using a message delivery delay based on characteristics detected in selected messages. Messages are evaluated for characteristics resembling unsolicited bulk email. A determination is made whether a message passing through the email system exhibits such characteristics and whether to delay the message. Suspect messages may be delayed for a period of time, the delay period being dependent on the characteristics giving rise to a determination to delay. Following the period, additional information received during the delay period characterizing the message is used to determine whether to dispose or deliver the message. Messages evaluated can be inbound to the email system, outbound to other email systems, or moving within the email system. Show less

Methods for assisting email users manage email messages received in an email account. An event is triggered by an action performed by an email user with respect to an email message in an email account. The event identifies an entity associated with the email message (e.g., sender address, domain, keyword, etc.). A determination is made whether to assist the user manage their email based on a heuristic. The heuristic assigns weights based on prior events associated with the same entity to… Show more

Methods for assisting email users manage email messages received in an email account. An event is triggered by an action performed by an email user with respect to an email message in an email account. The event identifies an entity associated with the email message (e.g., sender address, domain, keyword, etc.). A determination is made whether to assist the user manage their email based on a heuristic. The heuristic assigns weights based on prior events associated with the same entity to determine whether the user is interested in receiving emails from the sender. Based on the heuristics, the method may add the sender to the user's block-list or unsubscribe the user from a mailing list. Show less

In a distributed email system, user preferences respected more effectively by presenting messages marked for deletion to secondary messaging servers having access to user preferences. Messages marked for deletion by inbound servers are presented to secondary level servers having access to user white lists and the choice of whether to delete the suspect message is made by the secondary server.

Network entities controlling a set of nodes may vary by trustworthiness, such as tolerance for nodes that send spam, distribute malware, or perform denial-of-service attacks. A device receiving such activities may identify a trust rating of the network entity and apply appropriately stringent filtering (such as spam evaluation) to activities received from nodes controlled by the network entity. However, a poor trust rating of a network entity may subject a legitimate node controlled by the… Show more

Network entities controlling a set of nodes may vary by trustworthiness, such as tolerance for nodes that send spam, distribute malware, or perform denial-of-service attacks. A device receiving such activities may identify a trust rating of the network entity and apply appropriately stringent filtering (such as spam evaluation) to activities received from nodes controlled by the network entity. However, a poor trust rating of a network entity may subject a legitimate node controlled by the network entity to inefficiently or unfairly stringent activity filtering. Instead, the device may evaluate the activities of a particular node, assign a trust rating to the node, and if the trust rating of the node is higher than the trust rating of the network entity, apply less stringent activity filtering to the activities of the node, thereby “rescuing” the node from the more stringent activity filtering applied to the other nodes of the network entity. Show less

Presented herein are techniques for assigning trust ratings to network entities based on evaluations of activity of various nodes interacting with the device over the network, where such techniques may reduce the avoidance of blacklisting through the switching of network addresses. These techniques involve the mapping of ranges of network addresses (such as blocks of IP addresses) to a particular network entity. For example, the border gateway protocol (BGP) utilized by various network routers… Show more

Presented herein are techniques for assigning trust ratings to network entities based on evaluations of activity of various nodes interacting with the device over the network, where such techniques may reduce the avoidance of blacklisting through the switching of network addresses. These techniques involve the mapping of ranges of network addresses (such as blocks of IP addresses) to a particular network entity. For example, the border gateway protocol (BGP) utilized by various network routers to establish routes of data packets may identify one or more autonomous systems (ASes), each of which may have an autonomous system number (ASN), and each of which may be associated in a BGP routing table with network addresses comprising a network address group. For respective nodes of the network associated with a network entity (e.g., having a network address within the network address group of the network entity), activities of the node interacting with the device may be evaluated to determine the desirability of the activity. Moreover, a network entity trust rating may be assigned to the network entity based on the evaluated activities of the nodes controlled by the network entity. The network entity trust rating may then be used to determine a level of filtering of nodes controlled by the network entity (e.g., any node having a network address within the network address group associated with the network entity.) In this manner, the activities of a node may be attributed to many nodes controlled by the network entity, such that a perpetrator of undesirable activity may be unable to avoid filtering by switching to a different network address that is controlled by the same network entity (e.g., a different IP address associated with the same domain.) These techniques may be particularly effective because the routing tables stored by various routers according to the border gateway protocol (BGP) may be difficult for perpetrators to alter... Show less

A system and method of managing unsolicited email sent to an email system over a network. Email messages are received at an message at an inbound mail transfer agent. A determination is made as to whether the email message is suspected to be an unsolicited suspect message. One or more queries for additional information on one or more characteristics of the message is initiated. Determinations are made based on replies to the queries before issuing a message accepted for delivery indication to a… Show more

A system and method of managing unsolicited email sent to an email system over a network. Email messages are received at an message at an inbound mail transfer agent. A determination is made as to whether the email message is suspected to be an unsolicited suspect message. One or more queries for additional information on one or more characteristics of the message is initiated. Determinations are made based on replies to the queries before issuing a message accepted for delivery indication to a sending server Show less