Abstract: A system that incorporates a user context into a computer-based search is provided. To establish the context, the innovation can identify information about a user state or context via a variety of sources and sensors. The state/context information can be used to filter, arrange and/or rank search results so as to facilitate converging on meaningful searches and results. Machine learning systems (implicitly and/or explicitly trained) can be employed to infer a current and/or future context related to user. An identified or inferred user context can be employed to modify an automated or user-defined search input/query. Contextual cues can be considered directly in the construction and use of context of context-sensitive retrieval algorithms that are optimized for identifying and/or ranking of informational items of potential interest or value in different contexts. As well, the context can be employed to intelligently render results of a query (e.g., user/application defined, context-modified query).

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: The claimed subject matter provides systems and/or methods that facilitate diversifying search results to improve searching and/or personalized searching. An interface component can receive a query. Additionally, a result diversification component can modify diversity of a set of search results obtained by a search engine in response to a query based at least in part upon one or more dimensions of diversity. The dimensions of diversity can include document topic, document type, document genre, domain of document, document age, location associated with the document, commercial characteristics of the document, user intent, and the like.

Abstract: A system and methodology is provided for filtering temporal streams of information such as news stories by statistical measures of information novelty. Various techniques can be applied to custom tailor news feeds or other types of information based on information that a user has already reviewed. Methods for analyzing information novelty are provided along with a system that personalizes and filters information for users by identifying the novelty of stories in the context of stories they have already reviewed. The system employs novelty-analysis algorithms that represent articles as a bag of words and named entities. The algorithms analyze inter- and intra-document dynamics by considering how information evolves over time from article to article, as well as within individual articles.

Abstract: Most information retrieval systems start with a user's explicit query. Systems and methods are provided that perform implicit or background queries to one or more information sources based on the ongoing activities of users. The methods provide users with the results of such automated contextualized searches in an unobtrusive manner. In one aspect, implicit queries are run when users are reading, working on or composing an application. Queries can be automatically generated by analyzing an application, and results can be presented in a variety of peripheral display configurations, including a small pane adjacent to a current window to provide peripheral awareness of related information that is automatically determined from existing user context and/or related content from the application.

Abstract: The present invention relates to systems and methods providing content-access-based information retrieval. Information items from a plurality of disparate information sources that have been previously accessed or considered are automatically indexed in a data store, whereby a multifaceted user interface is provided to efficiently retrieve the items in a cognitively relevant manner. Various display output arrangements are possible for the retrieved information items including timeline visualizations and multidimensional grid visualizations. Input options include explicit, implicit, and standing queries for retrieving data along with explicit and implicit tagging of items for ease of recall and retrieval. In one aspect, an automated system is provided that facilitates concurrent searching across a plurality of information sources.

Abstract: Architecture for improving text searches using information redundancy. A search component is coupled with an analysis component to rerank documents returned in a search according to a redundancy values. Each returned document is used to develop a corresponding word probability distribution that is further used to rerank the returned documents according to the associated redundancy values. In another aspect thereof, the query component is coupled with a projection component to project answer redundancy from one document search to another. This includes obtaining the benefit of considerable answer redundancy from a second data source by projecting the success of the search of the second data source against a first data source.

Abstract: The invention applies a probabilistic approach to combining evidence regarding the correct classification of items. Training data and machine learning techniques are used to construct probabilistic dependency models that effectively utilize evidence. The evidence includes the outputs of one or more classifiers and optionally one or more reliability indicators. The reliability indicators are, in a broad sense, attributes of the items being classified. These attributes can include characteristics of an item, source of an item, and meta-level outputs of classifiers applied to the item. The resulting models include meta-classifiers, which combine evidence from two or more classifiers, and tuned classifiers, which use reliability indicators to inform the interpretation of classical classifier outputs. The invention also provides systems and methods for identifying new reliability indicators.

Abstract: An information retrieval system, including a learning and real-time classification methodology, is provided in accordance with the present invention. The system includes a hierarchal analysis component that receives a query and processes probabilities associated with N categories, each category having one or more topics, wherein N is an integer. An interactive component drives clarification dialog that is derived from the query and the probabilities associated with the N categories and the one or more topics. The clarification dialog, driven by a rule-based policy, a decision-theoretic analysis considering the costs of dialog to focus the results versus the costs of browsing larger lists, or combinations of rules and decision-theoretic analysis is employed when valuable to determine at least one category of the N categories to facilitate retrieval of at least one of the topics.

Abstract: Architecture for improving text searches using information redundancy. A search component is coupled with an analysis component to rerank documents returned in a search according to a redundancy values. Each returned document is used to develop a corresponding word probability distribution that is further used to rerank the returned documents according to the associated redundancy values. In another aspect thereof, the query component is coupled with a projection component to project answer redundancy from one document search to another. This includes obtaining the benefit of considerable answer redundancy from a second data source by projecting the success of the search of the second data source against a first data source.

Abstract: The present invention relates to systems and methods providing content-access-based information retrieval. Information items from a plurality of disparate information sources that have been previously accessed or considered are automatically indexed in a data store, whereby a multifaceted user interface is provided to efficiently retrieve the items in a cognitively relevant manner. Various display output arrangements are possible for the retrieved information items including timeline visualizations and multidimensional grid visualizations. Input options include explicit, implicit, and standing queries for retrieving data along with explicit and implicit tagging of items for ease of recall and retrieval. In one aspect, an automated system is provided that facilitates concurrent searching across a plurality of information sources.

Abstract: Most information retrieval systems start with a user's explicit query. Systems and methods are provided that perform implicit or background queries to one or more information sources based on the ongoing activities of users. The methods provide users with the results of such automated contextualized searches in an unobtrusive manner. In one aspect, implicit queries are run when users are reading, working on or composing an application. Queries can be automatically generated by analyzing an application, and results can be presented in a variety of peripheral display configurations, including a small pane adjacent to a current window to provide peripheral awareness of related information that is automatically determined from existing user context and/or related content from the application.

Abstract: Architecture for improving text searches using information redundancy. A search component is coupled with an analysis component to rerank documents returned in a search according to a redundancy values. Each returned document is used to develop a corresponding word probability distribution that is further used to rerank the returned documents according to the associated redundancy values. In another aspect thereof, the query component is coupled with a projection component to project answer redundancy from one document search to another. This includes obtaining the benefit of considerable answer redundancy from a second data source by projecting the success of the search of the second data source against a first data source.

Abstract: One or more models of memorability are provided that facilitate various computer-based applications including those centering on the storage, retrieval, and processing of information, applications that remind people about items they risk not recalling or overlooking, and facilitating communications of reminders. In one application, the models are used to help compose and navigate large personal stores of information about a user's activities, communications, images, and other content. In another application, views of files in directories are extended with the addition of memory landmarks, and a means for controlling the number of landmarks provided via changing a threshold on inferred memorability. Another application centers on the use of models of memorability to select subsets of images from larger sets representing events, for display in a slide show or ambient photo display.

Abstract: A graphical user interface in which object thumbnails are rendered on a simulated three-dimensional surface which (i) exploits spatial memory and (ii) allows more objects to be rendered on a given screen. The objects may be moved, continuously, on the surface with a two-dimensional input device. Furthermore, the interface determines a degree to which each such object is related, either through similarity or matching, to other such objects and displays an appropriate cue proximate to and associated with the former object to visually signify this degree.

Abstract: A text classifier and building the text classifier by determining appropriate parameters for the text classifier.

Abstract: A graphical user interface in which object thumbnails, as scaled images, are rendered on a two-dimensional wall or screen, and which exploits spatial memory. The objects may be moved, continuously, on the surface with a two-dimensional input device. Pop-up title bars may be rendered over active objects. Intelligent help may be provided to the user, as visual indicators, based on proximity clustering or based on matching algorithms.

Abstract: A technique, specifically a method and apparatus that implements the method, which through a probabilistic classifier (370) and, for a given recipient, detects electronic mail (e-mail) messages, in an incoming message stream, which that recipient is likely to consider "junk". Specifically, the invention discriminates message content for that recipient, through a probabilistic classifier (e.g., a support vector machine) trained on prior content classifications. Through a resulting quantitative probability measure, i.e., an output confidence level, produced by the classifier for each message and subsequently compared against a predefined threshold, that message is classified as either, e.g., spam or legitimate mail, and, e.g., then stored in a corresponding folder (223, 227) for subsequent retrieval by and display to the recipient.

Abstract: A methodology for retrieving textual data objects is disclosed. The information is treated in the statistical domain by presuming that there is an underlying, latent semantic structure in the usage of words in the data objects. Estimates to this latent structure are utilized to represent and retrieve objects. A user query is recouched in the new statistical domain and then processed in the computer system to extract the underlying meaning to respond to the query.