Abstract: The subject invention employs an indication gateway to provide a “buffer” between user indications (e.g., “clicks”) responsive to an interactive enticement such as, for example, a clickable online advertisement, and an entity associated with the enticement such as, for example, an online business. The indication gateway allows for subsequent checks on whether an initial user indication is sincere. Instances of the subject invention can accomplish this via additional information gathering, subsequent indication requirements, fraudulent indication tests, and/or buffering of subsequent indications, links, & content and the like. Additionally, instances of the subject invention can differentiate between different types of user indications and provide pricing structures based upon the differentiated types. This facilitates in providing a charging process for user indications to entities associated with the interactive enticement.

Abstract: A computer-implemented implicit querying system comprises a scanning component that scans content of a document. An analysis component analyzes the scanned content and outputs a query based at least in part upon the analysis and frequency of use information associated with the query. The system can further comprise a weighting component that provides weights to text within the document based at least in part upon location of text within the document. The query can then be output to a user based at least in part upon the provided weights.

Abstract: The subject invention provides a unique system and method that facilitates propagating selected advertisements among users of interactive services. Interactive service users can be targeted for specific types of advertisements for particular products or services. When a user selects at least one advertisement for more detailed viewing, the advertisement can be distributed to or shared with one or more other users. These other users may be part of the original user's social network. Thus user-selected advertisements can be shared among users who are familiar with each other's current or future interests. In some cases, user-selected advertisements can replace system-selected advertisements. As a result, advertisers can benefit from increased exposure of and interest in their advertisements.

Abstract: The subject invention provides a unique system and method that facilitates mitigation of storage abuse in connection with free storage provided by messaging service providers such as email, instant messaging, chat, blogging, and/or web hosting service providers. The system and method involve measuring the outbound volume of stored data. When the volume satisfies a threshold, a cost can be imposed on the account to mitigate the suspicious or abusive activity. Other factors can be considered as well that can modify the cost imposed on the cost such as by increasing the cost. Machine learning can be employed as well to predict a level or degree of suspicion. The various factors or the text of the messages can be used as input for the machine learning system.

Abstract: The subject invention provides a unique system and method that facilitates providing contextual advertisements based on one or more identified terms extracted from a non-text object such as an image, video, and/or audio object. Terms can also be identified and extracted from metadata associated with or other data derived from text objects such as email messages and attached text documents. One or more recognition techniques can be employed to identify data found in the non-text object (including the metadata or any other data derived therefrom) and data found in the metadata associated with the text object. Once the identified terms are analyzed, an appropriate contextual advertisement can be presented to the user. If the content of the non-text or text object is deemed of a negative nature, no contextual advertisement is provided.

Abstract: Email spam filtering is performed based on a combination of IP address and domain. When an email message is received, an IP address and a domain associated with the email message are determined. A cross product of the IP address (or portions of the IP address) and the domain (or portions of the domain) is calculated. If the email message is known to be either spam or non-spam, then a spam score based on the known spam status is stored in association with each (IP address, domain) pair element of the cross product. If the spam status of the email message is not known, then the (IP address, domain) pair elements of the cross product are used to lookup previously determined spam scores. A combination of the previously determined spam scores is used to determine whether or not to treat the received email message as spam.

Abstract: The subject invention provides a unique system and method that facilitates providing content-targeted advertising to a user based at least in part on the content of a user action. The user action can be performed in connection with an outbound messaging system, a real-time messaging system such as a chat or instant messaging, a game environment, and/or calendaring system. The system and method analyze at the least the content of an outbound message and then present a content-targeted advertisement based on the content of the message. The same can be done with respect to calendar entries. However, outbound and inbound calendar entries, invitations, and responses to invitations can be analyzed for content and have content-targeted advertisements presented to the sender or receiver of such items. User privacy can be maintained and/or increased by allowing a user to opt out of content-targeting advertisements. Reasons for being targeted can also be provided to the user.

Abstract: A streaming media caching mechanism and cache manager efficiently establish and maintain the contents of a streaming media cache for use in serving streaming media requests from cache rather than from an original data source when appropriate. The cost of caching is incurred only when the benefits of caching are likely to be experienced. The caching mechanism and cache manager evaluate the request count for each requested URL to determine whether the URL represents a cache candidate, and further analyze the URL request rate to determine whether the content associated with the URL will be cached. In an embodiment, the streaming media cache is maintained with a predetermined amount of reserve capacity rather than being filled to capacity whenever possible.

Abstract: Phishing detection, prevention, and notification is described. In an embodiment, a messaging application facilitates communication via a messaging user interface, and receives a communication, such as an email message, from a domain. A phishing detection module detects a phishing attack in the communication by determining that the domain is similar to a known phishing domain, or by detecting suspicious network properties of the domain. In another embodiment, a Web browsing application receives content, such as data for a Web page, from a network-based resource, such as a Web site or domain. The Web browsing application initiates a display of the content, and a phishing detection module detects a phishing attack in the content by determining that a domain of the network-based resource is similar to a known phishing domain, or that an address of the network-based resource from which the content is received has suspicious network properties.

Abstract: Phishing detection, prevention, and notification is described. In an embodiment, a messaging application facilitates communication via a messaging user interface, and receives a communication, such as an email message, from a domain. A phishing detection module detects a phishing attack in the communication by determining that the domain is similar to a known phishing domain, or by detecting suspicious network properties of the domain. In another embodiment, a Web browsing application receives content, such as data for a Web page, from a network-based resource, such as a Web site or domain. The Web browsing application initiates a display of the content, and a phishing detection module detects a phishing attack in the content by determining that a domain of the network-based resource is similar to a known phishing domain, or that an address of the network-based resource from which the content is received has suspicious network properties.

Abstract: Disclosed are signature-based systems and methods that facilitate spam detection and prevention at least in part by calculating hash values for an incoming message and then determining a probability that the hash values indicate spam. In particular, the signatures generated for each incoming message can be compared to a database of both spam and good signatures. A count of the number of matches can be divided by a denominator value. The denominator value can be an overall volume of messages sent to the system per signature for example. The denominator value can be discounted to account for different treatments and timing of incoming messages. Furthermore, secure hashes can be generated by combining portions of multiple hashing components. A secure hash can be made from a combination of multiple hashing components or multiple combinations thereof. The signature based system can also be integrated with machine learning systems to optimize spam prevention.

Abstract: Disclosed are systems and methods that facilitate securing communication channels used in a challenge-response system to mitigate spammer intrusion or deception. The systems and methods make use of unique IDs that can be added to outbound messages originating from a sender, a recipient, and a third-party server. The IDs can be correlated according to the relevant parties. Thus, for example, a sender can add a signed ID to an outgoing message. A challenge sent back to the sender for that particular message can echo the same ID or a new ID derived from the original ID to allow a sender to verify that the challenge corresponds to an actual message. The IDs can include cookies as well to facilitate correlation of messages and to facilitate the retrieval of messages once a sender is determined to be legitimate.

Abstract: The present invention provides a unique system and method that facilitates incrementally updating spam filters in near real time or real time. Incremental updates can be generated in part by difference learning. Difference learning involves training a new spam filter based on new data and then looking for the differences between the new spam filter and the existing spam filter. Differences can be determined at least in part by comparing the absolute values of parameter changes (weight changes of a feature between the two filters). Other factors such as frequency of parameters can be employed as well. In addition, available updates with respect to particular features or messages can be looked up using one or more lookup tables or databases. When incremental and/or feature-specific updates are available, they can be downloaded such as by a client for example. Incremental updates can be automatically provided or can be provided by request according to client or server preferences.

Abstract: A method describes user interaction in combination with sending a send item from an application of a computing device to a recipient. The computing device has an attestation unit thereon for attesting to trustworthiness. The application facilitates a user in constructing the send item, and pre-determined indicia are monitored that can be employed to detect that the user is in fact expending effort to construct the send item. The attestation unit authenticates the application to impart trust thereto, and upon the user commanding the application to send, a send attestation is constructed to accompany the send item. The send attestation is based on the monitored indicia and the authentication of the application and thereby describes the user interaction. The constructed send attestation is packaged with the constructed send item and the package is sent to the recipient.

Abstract: The subject invention provides for systems and methods that facilitate optimizing one or mores sets of training data by utilizing an Exponential distribution as the prior on one or more parameters in connection with a maximum entropy (maxent) model to mitigate overfitting. Maxent is also known as logistic regression. More specifically, the systems and methods can facilitate optimizing probabilities that are assigned to the training data for later use in machine learning processes, for example. In practice, training data can be assigned their respective weights and then a probability distribution can be assigned to those weights.

Abstract: The subject invention provides for systems and methods that facilitate optimizing one or mores sets of training data by utilizing an Exponential distribution as the prior on one or more parameters in connection with a maximum entropy (maxent) model to mitigate overfitting. Maxent is also known as logistic regression. More specifically, the systems and methods can facilitate optimizing probabilities that are assigned to the training data for later use in machine learning processes, for example. In practice, training data can be assigned their respective weights and then a probability distribution can be assigned to those weights.

Abstract: The present invention provides a unique system and method that can employ machine learning techniques to automatically fill one or more fields across a diverse array of web forms. In particular, one or more instrumented tools can collect input or entries of form fields. Machine learning can be used to learn what data corresponds to which fields or types of fields. The input can be sent to a central repository where other databases can be aggregated as well. This input can be provided to a machine learning system to learn how to predict the desired outputs. Alternatively or in addition, learning can be performed in part by observing entries and then adapting the autofill component accordingly. Furthermore, a number of features of database fields as well as constraints can be employed to facilitate assignments of database entries to form values—particularly when the web form has never been seen before by the autofill system.

Abstract: The present invention provides a unique system and method that can employ machine learning techniques to automatically fill one or more fields across a diverse array of web forms. In particular, one or more instrumented tools can collect input or entries of form fields. Machine learning can be used to learn what data corresponds to which fields or types of fields. The input can be sent to a central repository where other databases can be aggregated as well. This input can be provided to a machine learning system to learn how to predict the desired outputs. Alternatively or in addition, learning can be performed in part by observing entries and then adapting the autofill component accordingly. Furthermore, a number of features of database fields as well as constraints can be employed to facilitate assignments of database entries to form values—particularly when the web form has never been seen before by the autofill system.

Abstract: System and method for a sender of communications to comply with a predetermined time limit. Computer-executable instructions are adapted to receive an incoming communication from a recipient of communications. Computer-executable instructions are adapted to store data indicating a last time that the incoming communication is received by the sender. Computer-executable instructions are adapted to send a communication to the recipient if the stored data indicates that the time between the last time that the incoming communication is received by the sender and a present time does not exceed the predetermined time limit.

Abstract: The subject invention provides for systems and methods that facilitate optimizing one or mores sets of training data by utilizing an Exponential distribution as the prior on one or more parameters in connection with a maximum entropy (maxent) model to mitigate overfitting. Maxent is also known as logistic regression. More specifically, the systems and methods can facilitate optimizing probabilities that are assigned to the training data for later use in machine learning processes, for example. In practice, training data can be assigned their respective weights and then a probability distribution can be assigned to those weights.