Abstract: The subject invention provides a unique system and method that facilitates displaying content-targeted advertisements within applications running on an end-user or client computer. To mitigate privacy concerns, one or more advertisements can be stored on a client computer. At least one advertisement can be displayed on the client based at least in part on the context relating to the user's interaction with the client. By doing so, the user's private data or content is not passed to the server—meanwhile content-targeted advertising processing can be run on the user's content to determine which advertisements to display. Different forms of advertisements can be displayed to the user when the client is offline or online to facilitate optimizing use interaction with the advertisements and billing capabilities. To ensure that advertisements are displayed when content is displayed on a client, various encryption and decryption techniques can be employed to mitigate tampering of advertisement display code.

Abstract: A system and method for generating staged mixture model(s) is provided. The staged mixture model includes a plurality of mixture components each having an associated mixture weight, and, an added mixture component having an initial structure, parameters and associated mixture weight. The added mixture component is modified based, at least in part, upon a case that is undesirably addressed by the plurality of mixture components using a structural expectation maximization (SEM) algorithm to modify at the structure, parameters and/or associated mixture weight of the added mixture component. The staged mixture model employs a data-driven staged mixture modeling technique, for example, for building density, regression, and classification model(s). The basic approach is to add mixture component(s) (e.g., sequentially) to the staged mixture model using an SEM algorithm.

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 systems and methods that facilitate AIDS vaccine cocktail assembly via machine learning algorithms such as a cost function, a greedy algorithm, an expectation-maximization (EM) algorithm, etc. Such assembly can be utilized to generate vaccine cocktails for species of pathogens that evolve quickly under immune pressure of the host. For example, the systems and methods of the subject invention can be utilized to facilitate design of T cell vaccines for pathogens such HIV. In addition, the systems and methods of the subject invention can be utilized in connection with other applications, such as, for example, sequence alignment, motif discovery, classification, and recombination hot spot detection. The novel techniques described herein can provide for improvements over traditional approaches to designing vaccines by constructing vaccine cocktails with higher epitope coverage, for example, in comparison with cocktails of consensi, tree nodes and random strains from data.

Abstract: The subject invention leverages data sampling techniques to provide an efficient means to determine co-occurrence count estimations for objects and features from relational data, simplifying measure-of-association determinations. By providing an efficient mechanism to estimate co-occurrence counts, instances of the subject invention can be incorporated directly into a database, increasing its versatility and performance for such uses as collaborative filtering recommendations. Other instances of the subject invention can be utilized for enhancing database query selectivity, optimizing query performance through employment of á priori co-occurrence counts.

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: The subject invention provides systems and methods that facilitate AIDS vaccine cocktail assembly via machine learning algorithms such as a cost function, a greedy algorithm, an expectation-maximization (EM) algorithm, etc. Such assembly can be utilized to generate vaccine cocktails for species of pathogens that evolve quickly under immune pressure of the host. For example, the systems and methods of the subject invention can be utilized to facilitate design of T cell vaccines for pathogens such HIV. In addition, the systems and methods of the subject invention can be utilized in connection with other applications, such as, for example, sequence alignment, motif discovery, classification, and recombination hot spot detection. The novel techniques described herein can provide for improvements over traditional approaches to designing vaccines by constructing vaccine cocktails with higher epitope coverage, for example, in comparison with cocktails of consensi, tree nodes and random strains from data.

Abstract: The subject invention leverages scaleable itemsets and/or association rules to provide dynamic adjustment of memory usage. This allows the subject invention to provide association rules and/or itemsets with the highest support while utilizing a bounded amount of memory. Thus, a data analysis system and/or method utilizing the subject invention can self-adjust to provide the best association rules and/or itemsets based on available system resources. One instance of the subject invention employs dynamically adjustable minimum support values for data itemsets and/or association rules to facilitate in compensating for memory availability. In yet another instance of the subject invention a prefix tree data structure is utilized to facilitate in constructing itemsets. Memory utilization is then adjusted via pruning and/or reallocation of counter vectors and/or pointer vectors and/or reallocation of nodes of the prefix tree data structure for scaleable data itemsets and/or association rules.

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: Systems that facilitate immunogen design are described herein. An optimization component is provided to determine an immunogen according to at least one criterion. The immunogen comprises a set of overlapping sequences comprising sequences that are known to be and/or are likely to be immunogenic. At least one of the sequences that are likely to be immunogenic can be determined by analyzing associations between a host and a pathogen at a population level. Methods of determining an epitome are described herein. A plurality of sequences are received. At least one of the sequences is predicted to be an epitope based on a relationship between a diverse trait of a population and a mutation of a pathogen. A collection of the plurality of sequences is optimized according to one or more criteria to determine the epitome. Epitomes and immunogens determined by the systems and methods described herein are also contemplated.

Abstract: The subject invention leverages the conditional Gaussian (CG) nature of a continuous variable stochastic ARMAxp time series model to efficiently determine its parametric gradients. The determined gradients permit an easy means to construct a parametric structure for the time series model. This provides a gradient-based alternative to the expectation maximization (EM) process for learning parameters of the stochastic ARMAxp time series model. Thus, gradients for parameters can be computed and utilized with a gradient-based learning method for estimating the parameters. This allows values of continuous observations in a time series to be predicted utilizing the stochastic ARMAxp time series model, providing efficient and accurate predictions.

Abstract: Systems and method for managing a plurality of content items designated for placement in a particular position on a rendered page are provided. Methods in accordance with the present invention include receiving a plurality of content items, determining an initial placement allocation frequency for each content item, collecting performance data for one or more of the content items, and determining at least one additional allocation frequency in accordance with the performance data collected. Methods of the present invention may further include randomly allocating placement of each of the content items in the particular position on the page in accordance with one of the respective initial and/or additional allocation frequency for each content item. Additionally, the present invention provides systems and methods for automatically managing a plurality of content items to be displayed in a particular position on a rendered page such that value to the content provider may be maximized.

Abstract: Systems and methods for determining the value of bids placed by content providers for placement positions on a page, e.g., a web page, rendered according to a given context, for instance, the search results listing for a particular query initiated on a search engine web site, are provided. Additionally, systems and methods are provided for determining placement of content items, e.g., advertisements and/or images, on a rendered page relative to other content items on the page based upon bid value.

Abstract: Systems and methods for determining the value of bids placed by content providers for placement positions on a page, e.g., a web page, rendered according to a given context, for instance, the search results listing for a particular query initiated on a search engine web site, are provided. Additionally, systems and methods are provided for determining placement of content items, e.g., advertisements and/or images, on a rendered page relative to other content items on the page based upon bid value.

Abstract: Systems and methods for determining the value of bids placed by content providers for placement positions on a page, e.g., a web page, rendered according to a given context, for instance, the search results listing for a particular query initiated on a search engine web site, are provided. Additionally, systems and methods are provided for determining placement of content items, e.g., advertisements and/or images, on a rendered page relative to other content items on the page based upon bid value.

Abstract: Systems and methods for determining the value of bids placed by content providers for placement positions on a page, e.g., a web page, rendered according to a given context, for instance, the search results listing for a particular query initiated on a search engine web site, are provided. Additionally, systems and methods are provided for determining placement of content items, e.g., advertisements and/or images, on a rendered page relative to other content items on the page based upon bid value.

Abstract: The invention performs handwriting recognition using mixtures of Bayesian networks. A mixture of Bayesian networks (MBN) consists of plural hypothesis-specific Bayesian networks (HSBNs) having possibly hidden and observed variables. A common external hidden variable is associated with the MBN, but is not included in any of the HSBNs. Each HSBN models the world under the hypothesis that the common external hidden variable is in a corresponding one of its states. The MBNs encode the probabilities of observing the sets of visual observations corresponding to a handwritten character. Each of the HSBNs encodes the probabilities of observing the sets of visual observations corresponding to a handwritten character and given a hidden common variable being in a particular state.

Abstract: A technique for reducing a model database for use with handwriting recognizers. The model database is processed with a tuning set to identify a set of models that would result in the greatest character recognition accuracy. If further model database reduction is desired, the technique iteratively identifies smaller models that have the least adverse effect on the error rate. The technique continues identifying smaller models until a desired model database size has been achieved.

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.