Abstract: The present invention provides for generating inputs that can be provided to a message classification module to facilitate more reliable classification of electronic messages, such as, for example, as unwanted and/or unsolicited. In one embodiment, a sending messaging server provides an appropriate response to address verification data thereby indicating a reduced likelihood of the sending messaging server using a forged network address. In another embodiment, it is determined if a messaging server is authorized to send electronic messages for a domain. In yet another embodiment, electronic message transmission policies adhered to by a domain are identified. In yet a further embodiment, a sending computer system expends computational resources to solve a computational puzzle and includes an answer document in an electronic message. A receiving computer system receives the electronic message and verifies the answer document.

Abstract: Described herein is a system that facilitates assigning indications of usefulness to query suggestions. The system includes a query suggestion generator component that receives a query and generates a query suggestion based at least in part upon the received query. A model component outputs an indication of usefulness with respect to the query suggestion, wherein the model component is a machine-learned model of user behavior with respect to query suggestions.

Abstract: Described herein is a system that includes a receiver component that receives an indication that a user has accessed a search engine to initiate a search session. An analyzer component predicts informational interests of the user upon receipt of the indication and outputs an informational item that corresponds to the predicted informational interests of the user, wherein the analyzer component is configured to output the informational item prior to the user issuing a query to the search engine.

Abstract: The subject invention provides for a feedback loop system and method that facilitate classifying items in connection with spam prevention in server and/or client-based architectures. The invention makes uses of a machine-learning approach as applied to spam filters, and in particular, randomly samples incoming email messages so that examples of both legitimate and junk/spam mail are obtained to generate sets of training data. Users which are identified as spam-fighters are asked to vote on whether a selection of their incoming email messages is individually either legitimate mail or junk mail. A database stores the properties for each mail and voting transaction such as user information, message properties and content summary, and polling results for each message to generate training data for machine learning systems. The machine learning systems facilitate creating improved spam filter(s) that are trained to recognize both legitimate mail and spam mail and to distinguish between them.

Abstract: The present invention provides for generating inputs that can be provided to a message classification module to facilitate more reliable classification of electronic messages, such as, for example, as unwanted and/or unsolicited. In one embodiment, a sending messaging server provides an appropriate response to address verification data thereby indicating a reduced likelihood of the sending messaging server using a forged network address. In another embodiment, it is determined if a messaging server is authorized to send electronic messages for a domain. In yet another embodiment, electronic message transmission policies adhered to by a domain are identified. In yet a further embodiment, a sending computer system expends computational resources to solve a computational puzzle and includes an answer document in an electronic message. A receiving computer system receives the electronic message and verifies the answer document.

Abstract: A search query transformation system and method for transforming and refining a search query are described. Embodiments of the system and method use various graphical components and controls. Direct manipulation ensures that the searcher is driving the changes in the search queries using a pointing device. Embodiments of the search query transformation system and method include a search query re-weighting user interface (UI) component for graphically adjusting and re-weighting weights of search terms, and a search query term replacement UI component for graphically replacing a search term in a query or add a synonym to the query. Embodiments of the system and method also include a search query suggestion component, which provides query revision recommendations to a searcher that are tailored to the direct manipulation query refinement interface.

Abstract: The subject invention provides for an intelligent quarantining system and method that facilitates a more robust classification system in connection with spam prevention. The invention involves holding back some messages that appear to be questionable, suspicious, or untrustworthy from classification (as spam or good). In particular, the filter lacks information about these messages and thus classification is temporarily delayed. This provides more time for a filter update to arrive with a more accurate classification. The suspicious messages can be quarantined for a determined time period to allow more data to be collected regarding these messages. A number of factors can be employed to determine whether messages are more likely to be flagged for further analysis. User feedback by way of a feedback loop system can also be utilized to facilitate classification of the messages. After some time period, classification of the messages can be resumed.

Abstract: The present invention involves a system and method that facilitate identifying human interaction by utilizing HIPs such as order-based HIPs and determining a difficulty rating of any type of HIPs in an automated fashion. Order-based HIPs require a user to identify elements in the sequence as well as to identify a correct order of the elements in the sequence. The invention involves presenting a user with at least two HIPs such that the HIP can be of known and/or unknown difficulty. A user that correctly answers the HIP of known difficulty gains access to the HIP-controlled resource, action or application. The user's response to the HIP of unknown difficulty can then be examined and employed to determine whether that HIP is too difficult for humans to solve. Alternatively, at least one HIP can be presented. Difficulty of individual HIP parameters can also be determined.

Abstract: Aspects of the subject matter described herein relate to predicting and using search engine switching behavior. In aspects, switching components receive a representation of user interactions with at least one browser. The switching components derive information from the representation that is useful in predicting whether a user will switch search engines. The derived information and information about a user's current interaction with a browser is then used by a switch predictor to predict whether the user will switch search engines. This prediction may be used in a variety of ways examples of which are given herein.

Abstract: The subject invention provides systems and methods that facilitate obfuscating a spam filtering system to hinder reverse engineering of the spam filters and/or to mitigate spammers from finding a message that consistently gets through the spam filters almost every time. The system includes a randomization component that randomizes a message score before the message is classified as spam or non-spam so as to obscure the functionality of the spam filter. Randomizing the message score can be accomplished in part by adding a random number or pseudo-random number to the message score before it is classified as spam or non-spam. The number added thereto can vary depending on at least one of several types of input such as time, user, message content, hash of message content, and hash of particularly important features of the message, for example. Alternatively, multiple spam filters can be deployed rather than a single best spam filter.

Abstract: Network domain reputation-based spam filtering is described. In an embodiment, emails are received from a network domain and a reputation of the network domain is established. Additional emails are filtered as they are received to determine a status of each email as spam email or not spam email. An email can be determined to be a spam email based on any one or more of the reputation of the network domain, an authentication status of an email, and other information that can be derived from an email.

Abstract: Architecture for detecting and removing obfuscating clutter from the subject and/or body of a message, e.g., e-mail, prior to filtering of the message, to identify junk messages commonly referred to as spam. The technique utilizes the powerful features built into an HTML rendering engine to strip the HTML instructions for all non-substantive aspects of the message. Pre-processing includes pre-rendering of the message into a final format, which final format is that which is displayed by the rendering engine to the user. The final format message is then converted to a text-only format to remove graphics, color, non-text decoration, and spacing that cannot be rendered as ASCII-style or Unicode-style characters. The result is essentially to reduce each message to its common denominator essentials so that the junk mail filter can view each message on an equal basis.

Abstract: The subject invention provides for an intelligent quarantining system and method that facilitates detecting and preventing spam. In particular, the invention employs a machine learning filter specifically trained using origination features such as an IP address as well as destination feature such as a URL. Moreover, the system and method involve training a plurality of filters using specific feature data for each filter. The filters are trained independently each other, thus one feature may not unduly influence another feature in determining whether a message is spam. Because multiple filters are trained and available to scan messages either individually or in combination (at least two filters), the filtering or spam detection process can be generalized to new messages having slightly modified features (e.g., IP address). The invention also involves locating the appropriate IP addresses or URLs in a message as well as guiding filters to weigh origination or destination features more than text-based features.

Abstract: Disclosed are systems and methods that facilitate spam detection and prevention at least in part by building or training filters using advanced IP address and/or URL features in connection with machine learning techniques. A variety of advanced IP address related features can be generated from performing a reverse IP lookup. Similarly, many different advanced URL based features can be created from analyzing at least a portion of any one URL detected in a message.

Abstract: A dependency structure is used to divide samples corresponding to items to be ranked into leaf nodes, based on the rank of the items. The dependency structure is trained by splitting or merging training data received at given nodes based on selected features and selected thresholds for those features. A metric is then calculated which is indicative of performance of the node, in splitting the data. The trained structure is then used during runtime to rank items.

Abstract: The present invention provides for generating inputs that can be provided to a message classification module to facilitate more reliable classification of electronic messages, such as, for example, as unwanted and/or unsolicited. In one embodiment, a sending messaging server provides an appropriate response to address verification data thereby indicating a reduced likelihood of the sending messaging server using a forged network address. In another embodiment, it is determined if a messaging server is authorized to send electronic messages for a domain. In yet another embodiment, electronic message transmission policies adhered to by a domain are identified. In yet a further embodiment, a sending computer system expends computational resources to solve a computational puzzle and includes an answer document in an electronic message. A receiving computer system receives the electronic message and verifies the answer document.

Abstract: A model-based system and method for global optimization that utilizes quantum mechanics in order to approximate the global minimum of a given problem (e.g., mathematical function). A quantum mechanical particle with a sufficiently large mass has a ground state solution to the Schrödinger Equation which is localized to the global minimum of the energy field, or potential, it experiences. A given function is modeled as a potential, and a quantum mechanical particle with a sufficiently large mass is placed in the potential. The ground state of the particle is determined, and the probability density function of the ground state of the particle is calculated. The peak of the probability density function is localized to the global minimum of the potential.

Abstract: Distribution displays for categories are provided which illuminate the distribution of continuous attributes over all cases in a category, and which provide a histogram of the population of the different states of categorical attributes. An array of such displays by attribute (in one dimension) and category (in another dimension) may be provided. Category diagram displays are also provided for visualizing the different categories, and their distributions, populations, and similarities. These are displayed through different shading of nodes and edges representing categories and the relationship between two categories, and through proximity of nodes.

Abstract: The present invention involves a system and method that facilitate extracting data from messages for spam filtering. The extracted data can be in the form of features, which can be employed in connection with machine learning systems to build improved filters. Data associated with origination information as well as other information embedded in the body of the message that allows a recipient of the message to contact and/or respond to the sender of the message call be extracted as features. The features, or a subset thereof, can be normalized and/or deobfuscated prior to being employed as features of the machine learning systems. The (deobfuscated) features can be employed to populate a plurality of feature lists that facilitate spam detection and prevention. Exemplary features include an email address, an IP address, a URL, an embedded image pointing to a URL, and/or portions thereof.

Abstract: The invention relates to a system for filtering messages—the system includes a seed filter having associated therewith a false positive rate and a false negative rate. A new filter is also provided for filtering the messages, the new filter is evaluated according to the false positive rate and the false negative rate of the seed filter, the data used to determine the false positive rate and the false negative rate of the seed filter are utilized to determine a new false positive rate and a new false negative rate of the new filter as a function of threshold. The new filter is employed in lieu of the seed filter if a threshold exists for the new filter such that the new false positive rate and new false negative rate are together considered better than the false positive and the false negative rate of the seed filter.