Abstract: Personalized navigation for one or more individuals' use of a search engine is provided. Identification of a query submitted to the search engine is performed. If the query is identified to be a personal navigational query, which is a query via which the individuals intend to navigate to a particular site or information object that they have previously viewed, the particular site or information object associated with the query is identified, and results of the search are personalized based on knowledge of the identified site or information object.

Abstract: Concepts and technologies are described herein for hyperlocal smoothing. The hyperlocal smoothing solutions described herein provide a smooth view of data and events across hyperlocal geographic areas by combining sparse data available with inferred or extrapolated data. Additionally, the hyperlocal smoothing solutions described herein make use of contextual analysis to interpret service requests in a manner appropriate for a targeted hyperlocal area. Thus, the smooth view of data can be queried in a contextually sensitive manner to return relevant information for a hyperlocal geographic area, even in circumstances wherein data relevant to the hyperlocal geographic area is sparse or even non-existent.

Abstract: Multiple pieces of information can be arranged into a single construct that allows the employee to ascertain information quickly while at her workstation. Selection of information for placement into the construct can employ various statistical models and the like. Selective pieces of information can be masked for a user's construct based upon access rights of the user. Constructs can be configured by a user based on personal preferences as well as by an administrator. Population of metadata upon the construct can be performed automatically through an instruction of the administrator or be overridden by a user request. In addition, various types of synchronization can be implemented between constructs, such that identical or near-identical information is populated upon multiple constructs.

Abstract: Architecture for presenting advertisements in realtime in retail establishments. A sensor component includes sensors for collecting information about a customer or group of customers as they move through the store. The sensors can include capability for image processing, audio processing, light sensing, velocity sensing, direction sensing, proximity sensing, face recognition, pose recognition, transaction recognition, and biometric sensing, for example. A customer component analyzes the information and generates a profile about the customer. Advertisements are selected for presentation that target the customers as they walk in proximity of a presentation system of the store. An advertisement component facilitates dynamic presentation of a targeted advertisement to the individual as a function of the profile. The customer component can infer information during analysis using machine learning and reasoning.

Abstract: A query processing system is described herein for personalizing results for a particular user. The query processing system operates by receiving a query from a particular user u who intends to find results that satisfy the query with respect to a topic Tu, the user being characterized by user information ?u. In one implementation, the query processing system then produces a generic topic distribution Prr(T|q) associated with the query that is germane to a population of generic users, as well as a user-specific query-dependent topic distribution Pr(Tu|q,?u) for the particular user. The query processing system then produces personalized results for the particular user based on Prr(T|q) and Pr(Tu|q,?u). The query processing system can use multiple techniques to produce Pr(Tu|q,?u), such as, in one approach, a discriminative learning approach.

Abstract: Providing for generation of a task oriented data structure that can correlate natural language descriptions of computer related tasks to application level commands and functions is described herein. By way of example, a system can include an activity translation component that can receive a natural language description of an application level task. Furthermore, the system can include a language modeling component that can generate the data structure based on an association between the description of the task and at least one application level command utilized in executing the computer related task. Once generated, the data structure can be utilized to automate computer related tasks by input of a human centric description of those tasks. According to further embodiments, machine learning can be employed to train classifiers and heuristic models to optimize task/description relationships and/or tailor such relationships to the needs of particular users.

Abstract: Content management architecture for a portable wireless device. Caching and fetching techniques are provided to improve content handling for portable devices such as cellular telephones and portable computers. A search component automatically performs searches as a background process, and potentially desired content is received and cached by a content storing component to be available in the future when and if needed, mitigating latency associated with slow download speeds, refresh rates, and other system and/or network impediments. Content from background search results can be trickled into the device as part of the background process so as not to burden system resources for other processes. As part of memory management, aged and/or low priority or low interest content can be selectively removed or archived to increase available cache or memory space, as well as to maintain relevant content within the device. A presentation component facilitates presentation of the pre-stored content.

Abstract: One or more techniques and/or systems are provided for transitioning between representations of an electronic document. Elements, such as visual elements, common between a first set of elements from a first representation of the document and a second set of elements from a second representation of the document are identified. The non-intersecting elements from the first and second sets are respectively ranked in accordance with a representation relevance. First set non-intersecting elements are removed from an intermediate representation of the document, and second set non-intersecting elements are added to the intermediate representation, while the intermediate representation is not equivalent to the second representation; and respective iterations of the intermediate representation are output, such as to a display to depict a transition from the first representation of the document to the second representation of the document.

Abstract: The subject disclosure is directed towards using cursor activity with respect to search result pages to enhance search engine operation. Data associated with the cursor activity may be translated into cursor events representing user interactions with a search result page. Based on the cursor events, user behavior indicia may be identified via a user intent prediction model corresponding to various search result page related user actions. The user behavior indicia and/or the user intent prediction model may be used to produce search result pages for current search queries from the user.

Abstract: The subject disclosure pertains to anonymous network interaction. More specifically, mechanisms are provided to ensure anonymity with respect network interaction such that third parties are unable to determine the source and/or intent of communications. Accordingly, entities may anonymize all outgoing and/or incoming data packets so as to mitigate outside entities from learning about information being sought and/or provided. For example, a user or corporation may employ an anonymizer with respect to web searching so that outside entities are not able to determine what information is attempted to be accessed and by whom.

Abstract: Techniques provide time-aware ranking, such as ranking of information, files or URL (uniform resource locator) links. For example, time-aware modeling assists in determining user intent of a query to a search engine. In response to the query, results are ranked in a time-aware manner to better match the user intent. The ranking may model query, URL and query-URL pair behavior over time to create time-aware query, URL and query-URL pair models, respectively. Such models may predict behavior of a query-URL pair, such as frequency and timing of clicks to the URL of the pair when the query of the pair is posed to the search engine. Results of a query may be ranked by predicted query-URL behavior. Once ranked, the results may be sent to the user in response to the query.

Abstract: A user's domain expertise may be estimated through several factors by monitoring different aspects of a user's interaction with a web browser. Based on the user's domain expertise, search results may be presented to the user that is commensurate with their expertise, resulting in a more efficient and productive on line session. A user's expertise in a knowledge domain may be determined from the user's behavior, including analyzing search queries, monitoring how the user navigates between and through websites, and analyzing the specific cites visited. As a user interacts with a browser, the user's estimated domain expertise may be updated and used to provide appropriate and useful search results. In many embodiments, a user may have different expertise levels for different technical domains.

Abstract: The claimed subject matter relates to an architecture that can facilitate creation and management of an event-oriented transient network and can further manage decommission of the transient network. In particular, the architecture can construct temporary communities based upon a particular event, project, or activity; manage (e.g., filter, prioritize, or control) communications and content associated with the community; and disband the community by deconstructing the transient network according to an aging function that controls how the network decays. In addition, the architecture can leverage existing information (e.g. profile data) and content feeds associated with disparate social networking services or communities for the benefit of the temporary community.

Abstract: A query processing system is described herein for personalizing results for a particular user. The query processing system operates by receiving a query from a particular user u who intends to find results that satisfy the query with respect to a topic Tu, the user being characterized by user information ?u. In one implementation, the query processing system then produces a generic topic distribution Prr(T|q) associated with the query that is germane to a population of generic users, as well as a user-specific query-dependent topic distribution Pr(Tu|q,?u) for the particular user. The query processing system then produces personalized results for the particular user based on Prr(T|q) and Pr(Tu|q,?u). The query processing system can use multiple techniques to produce Pr(Tu|q,?u), such as, in one approach, a discriminative learning approach.

Abstract: Architecture is provided that facilitates user-controlled access to user profile information related to spam filtering. A user is allowed to selectively expose (or mask) portions of his/her profile related to spam filtering to third parties. Additionally, advertisers and/or content providers can offer incentives or enticement in response to the acceptance of which a user exposes larger portions of their profiles related to spam filtering. The architecture comprises a system that facilitates profile management utilizing a profile component that facilitates creation and storage of an electronic profile including spam filtering information of a user, and a control component under control of the user for controlling access to the profile.

Abstract: Personalization is enabled in a privacy-conscious manner. User interest information can be determined as a function of user behavior with respect interaction with content, for example. Such private information can subsequently be disseminated in a controlled fashion based on permission of the user to which the information pertains. Additionally, core functionality can be supplemented by third-party extensions allowed by a user.

Abstract: Concepts and technologies are described herein for authority ranking for real time and social search. An authority index configured to store data relating to sources is generated. Data relating to the sources, including an authority value, are generated and stored at the authority index. The authority value may be defined as a function of source, topic, and point of view (“POV”), as well as other data, if desired, and may be determined based upon one or more ranking functions. The ranking functions are determined, and data corresponding to the ranking functions is obtained. Each of the ranking functions may be weighted according to a weighting function, a confidence value or interval, one or more time functions, and/or other methods. The obtained authority value may be used for affecting ranking of search results or for other purposes.

Abstract: Providing for generating an executive report of business or personal activity is described herein. By way of example, such executive report can identify a change and related cause with respect to a prior report. As a particular example, an inference engine can receive an activity report and reference prior reports to identify the change and related cause. A set of results containing such information can be provided to a synthesis component that can include and highlight such information in the executive report. In addition, additional sources of data can be referenced in order to include and/or customize the report to a particular individual, organization, culture, or the like. As described, aspects of the subject innovation can provide an executive report highlighting important aspects of data and tailoring those aspects to interests of one or more users.

Abstract: The subject disclosure is directed towards building one or more context and query models representative of users' search interests based on their logged interaction behaviors (context) preceding search queries. The models are combined into an intent model by learning an optimal combination (e.g., relative weight) for combining the context model with a query model for a query. The resultant intent model may be used to perform a query-related task, such as to rank or re-rank online search results, predict future interests, select advertisements, and so forth.

Abstract: A user's domain expertise may be estimated through several factors by monitoring different aspects of a user's interaction with a web browser. Based on the user's domain expertise, search results may be presented to the user that is commensurate with their expertise, resulting in a more efficient and productive on line session. A user's expertise in a knowledge domain may be determined from the user's behavior, including analyzing search queries, monitoring how the user navigates between and through websites, and analyzing the specific cites visited. As a user interacts with a browser, the user's estimated domain expertise may be updated and used to provide appropriate and useful search results. In many embodiments, a user may have different expertise levels for different technical domains.