Abstract: A random walk is performed over a graph, such as an augmented bipartite graph, relating to ownership data with respect to a plurality of users and items owned; the graph can provide social links between the users as well. Items can be recommended to users who do not own the items by randomly walking the graph starting at the user node to which the recommendation will be given. The random walk can step from user to user or from user to item; when an item is reached, the node can be absorbing such that the random walk terminates. The arrived item is recommended to the user. Parameters can also be provided to affect decisions made during the walk about which users to walk to and/or whether to walk to a user or an item.

Abstract: A system that can analyze a multi-dimensional input thereafter establishing a search query based upon extracted features from the input. In a particular example, an image can be used as an input to a search mechanism. Pattern recognition and image analysis can be applied to the image thereafter establishing a search query that corresponds to features extracted from the image input. The system can also facilitate indexing multi-dimensional searchable items thereby making them available to be retrieved as results to a search query. More particularly, the system can employ text analysis, pattern and/or speech recognition mechanisms to extract features from searchable items. These extracted features can be employed to index the searchable items.

Abstract: For a multi-party advertising exchange including advertising and publishing entities, each participant specifies tax rate(s), such as import tax and export tax, that apply to at least one other entity in the exchange. Since tax rate(s) can be expressed in different transactional terms by different parties, each tax rate is reduced to a common tax rate expression within the exchange for comparison. Intelligent tax rate selection and support can be provided to dynamically set tax rates that achieve utilitarian goals for the individual participants taking into account the tax rates expressed by other participants and their respective advertising goals, and dynamically adjusting tax rates over time in response to condition changes. Various refinements are provided and disclosed according to a host of optional implementations.

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 present invention provides systems and methods for obtaining information from a networked system utilizing a distributed web crawler. The distributed nature of clients of a server is leveraged to provide fast and accurate web crawling data. Information gathered by a server's web crawler is compared to data retrieved by clients of the server to update the crawler's data. In one instance of the present invention, data comparison is achieved by utilizing information disseminated via a search engine results page. In another instance of the present invention, data validation is accomplished by client dictionaries, emanating from a server, that summarize web crawler data. The present invention also facilitates data analysis by providing a means to resist spoofing of a web crawler to increase data accuracy.

Abstract: A user working on a client computer is allowed to remotely login to a server over a computer network. A first secure connection is established between the client and the server. Communications with a trusted device which is in the user's control is established via a communication channel between the trusted device and the client, where this channel is not part of the network. A second secure connection is established between the trusted device and the server through the client, where this second secure connection is tunneled within the first secure connection. The user remotely logs into the server over the second secure connection using the trusted device.

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: Methods and systems are disclosed for learning a regression decision graph model using a Bayesian model selection approach. In a disclosed aspect, the model structure and/or model parameters can be learned using a greedy search algorithm applied to grow the model so long as the model improves. This approach enables construction of a decision graph having a model structure that includes a plurality of leaves, at least one of which includes a non-trivial linear regression. The resulting model thus can be employed for forecasting, such as for time series data, which can include single or multi-step forecasting.

Abstract: The claimed subject matter is directed to the use of an application reputation service to assist users with minimizing their computerized machines' exposure to and infection from malware. Specifically, the claimed subject matter provides a method and system of an application reputation service that contains the reputations for elements that are known to be non-malicious as well as those known to be malicious. One embodiment of the claimed subject matter is implemented as a method to determine the reputation of an element (e.g., an application). When a user attempts to install or execute a new application, the Application Reputation Service is queried by the user's machine with a set of identities for the element. The Application Reputation Service determines the reputation of the application by referencing a knowledge base of known reputations and returns an indication (e.g., an overall rating, or a flag) of how safe that application would be to install and run on the user's computer.

Abstract: A “Quality-Based Ad Pricer” prices ads as a function of how users respond to a particular page and/or domain to which they are sent by an online advertisement. User experience is improved by ensuring that advertisements that are more relevant to a user are priced less than an ads which are less relevant to the user. In particular, a quality factor for each ad is determined as a property of the advertiser's site based on measured user behaviors with respect to that site. This quality factor is then used in ranking, selecting, and pricing ads in an automated online auction. Further, while ad aggregators are not excluded from the ad market by the pricing rules of the Quality-Based Ad Pricer, these rules ensure that there is a “level playing field” such that ads of merchants are not excluded by the ads of ad aggregators.

Abstract: The claimed matter provides systems and/or methods that enable sellers and buyers to take mutual advantage of the relationship of the location of seller outlets to routes that mobile buyers take to other destinations. The system can include devices that identify sellers capable of fulfilling a buyer's product or service requirements, generate value functions for the seller based on bidding functions acquired from the seller and related to the product or service requirements of the buyer, compare the value functions associated with multiple sellers to identify a successful seller, and notify the buyer of the location of the successful seller by modifying a route to a pre-established destination to include directions to the successful seller.

Abstract: Two methods for measuring keyword-document relevance are described. The methods receive a keyword and a document as input and output a probability value for the keyword. The first method is a similarity-based approach which uses techniques for measuring similarity between two short-text segments to measure relevance between the keyword and the document. The second method is a regression-based approach based on an assumption that if an out-of-document phrase (the keyword) is semantically similar to an in-document phrase, then relevance scores of the in and out-of document phrases should be close to each other.

Abstract: Improving object organization by presenting controlling attribute-specific lists is disclosed. For example, the object can be an email and the controlling attribute the sender of the email. Sender-specific lists are dynamically maintained and can include the most recent folders into which email have been moved. When a current email is selected, or when the user otherwise so indicates, a sender-specific list for the sender of the current email is displayed to the user. The user can select one of the folders from the list into which to move the current email. Besides email, the object can be a file, such that the controlling attribute can be the creator of the file.

Abstract: The present invention provides collaborative filtering systems and methods employing statistical smoothing to provide quickly creatable models that can efficiently predict probability that a user likes an item and/or similarities between items. Smoothing is accomplished by utilizing statistical methods such as support cutoff, single and multiple prior on counts, and prior on measure of association and the like. By improving model-based collaborative filtering with such techniques, performance is increased with regard to product-to-product recommendations. The present invention also provides improvements over systems based on dependency nets (DN) in both areas of quality of recommendations and speed of model creation. It can also be complementary to DN to improve the value of an existing collaborative filtering system's overall efficiency. It is also employable with low frequency user preference data.

Abstract: A computer-implemented system that facilitates establishing price(s) associated with items comprises a clustering component that clusters a collection of non-identical items into one or more sets of non-identical items. A pricing component receives one or more of active bids and stored bids and simulates an auction of at least one non-identical item within one of the one or more sets of non-identical items as if the non-identical items within the set were identical to determine price(s) associated with the at least one non-identical item. For example, the items can be at least portions of search terms received by a search engine.

Abstract: A multi-modal search system (and corresponding methodology) that employs wildcards is provided. Wildcards can be employed in the search query either initiated by the user or inferred by the system. These wildcards can represent uncertainty conveyed by a user in a multi-modal search query input. In examples, the words “something” or “whatchamacallit” can be used to convey uncertainty and partial knowledge about portions of the query and to dynamically trigger wildcard generation.

Abstract: A multi-modal search system (and corresponding methodology) is provided. The system employs text, speech, touch and gesture input to establish a search query. Additionally, a subset of the modalities can be used to obtain search results based upon exact or approximate matches to a search result. For example, wildcards, which can either be triggered by the user or inferred by the system, can be employed in the search.

Abstract: A multi-modal search query refinement system (and corresponding methodology) is provided. In accordance with the innovation, query suggestion results represent a word palette which can be used to select strings for inclusion or exclusion from a refined set of results. The system employs text, speech, touch and gesture input to refine a set of search query results. Wildcards can be employed in the search either prompted by the user or inferred by the system. Additionally, partial knowledge supplemented by speech can be employed to refine search results.

Abstract: Multimedia playback technique embodiments are presented which facilitate the playback of an arbitrary media recording during a multi-party communication over a real-time multi-way communication system via a user's communication device. The recorded media can be interjected into a multi-party communication on a real time basis. This is generally accomplished by the media recording being inserted into a media stream being processed by the user's communication device as part of the multi-party communication. This can be done by either replacing a portion of the media stream with the media recording or mixing the media recording with a portion of the media stream. Once inserted, the media recording is transmitted as part of the media stream to a least one other party to the communication.

Abstract: The subject invention leverages standard probabilistic inference techniques to determine a log-likelihood for a conditional Gaussian graphical model of a data set with at least one continuous variable and with data not observed for at least one of the variables. This provides an efficient means to compute gradients for CG models with continuous variables and incomplete data observations. The subject invention allows gradient-based optimization processes to employ gradients to iteratively adapt parameters of models in order to improve incomplete data log-likelihoods and identify maximum likelihood estimates (MLE) and/or local maxima of the incomplete data log-likelihoods. Conditional Gaussian local gradients along with conditional multinomial local gradients determined by the subject invention can be utilized to facilitate in providing parameter gradients for full conditional Gaussian models.