Abstract: An interactive concept learning image search technique that allows end-users to quickly create their own rules for re-ranking images based on the image characteristics of the images. The image characteristics can include visual characteristics as well as semantic features or characteristics, or may include a combination of both. End-users can then rank or re-rank any current or future image search results according to their rule or rules. End-users provide examples of images each rule should match and examples of images the rule should reject. The technique learns the common image characteristics of the examples, and any current or future image search results can then be ranked or re-ranked according to the learned rules.

Abstract: A method for managing windows in a display is disclosed. The method comprises forming clippings for windows located in a focal region of a display; displaying the clippings in a peripheral region of the display; hiding the windows in the focal region of the display; indicating the states of the clippings; and in response to a user action, displaying the windows and hiding the clippings. A clipping comprises an image of a region of a window and an icon. A clipping is formed when a window is dragged from the focal region into the peripheral region or when the minimize button of a window is clicked. A clipping list is formed when a clipping is moved near another clipping. A clipping moved near a clipping list is inserted into the clipping list.

Abstract: A multiple model data exploration system and method for running multiple machine-learning models simultaneously to understand and explore data. Embodiments of the system and method allow a user to gain a greater understanding of the data and to gain new insights into their data. Embodiments of the system and method also allow a user to interactively explore the problem and to navigate different views of data. Many different classifier training and evaluation experiments are run simultaneously and results are obtained. The results are aggregated and visualized across each of the experiments to determine and understand how each example is classified for each different classifier. These results then are summarized in a variety of ways to allow users to obtain a greater understanding of the data both in terms of the individual examples themselves and features associated with the data.

Abstract: Reaction information of participants to an interaction may be sensed and analyzed to determine one or more reactions or dispositions of the participants. Feedback may be provided based on the determined reactions. The participants may be given an opportunity to opt in to having their reaction information collected, and may be provided complete control over how their reaction information is shared or used.

Abstract: A system that can enable the atomization of application functionality in connection with an activity-centric system is provided. The system can be utilized as a programmatic tool that decomposes an application's constituent functionality into atoms thereafter monitoring and aggregating atoms with respect to a particular activity. In doing so, the functionality of the system can be scaled based upon complexity and needs of the activity. Additionally, the system can be employed to monetize the atoms or activity capabilities based upon respective use.

Abstract: An interactive tool is described for modifying the behavior of a system, such as, but not limited to, the behavior of a classification system. The tool uses an interface mechanism to present a current global state of the system. The tool accepts one or more refinements to this global state, e.g., by accepting individual changes to parameter settings that are presented by the interface mechanism. Based on this input, the tool computes and displays the global implications of the updated parameter settings. The process of iterating over one or more cycles of user updates, followed by computation and display of the implications of the attempted refinements, has the effect of advancing the system towards a global state that exhibits desirable behavior.

Abstract: A system that can enable the atomization of application functionality in connection with an activity-centric system is provided. The system can be utilized as a programmatic tool that decomposes an application's constituent functionality into atoms thereafter monitoring and aggregating atoms with respect to a particular activity. In doing so, the functionality of the system can be scaled based upon complexity and needs of the activity. Additionally, the system can be employed to monetize the atoms or activity capabilities based upon respective use.

Abstract: Described is using the human body as an input mechanism to a computing device. A sensor set is coupled to part of a human body. The sensor set detects mechanical (e.g., bio-acoustic) energy transmitted through the body as a result of an action/performed by the body, such as a user finger tap or flick. The sensor output data (e.g., signals) are processed to determine what action was taken. For example, the gesture may be a finger tap, and the output data may indicate which finger was tapped, what surface the finger was tapped on, or where on the body the finger was tapped.

Abstract: Described herein is a system that includes a receiver component that receives gesture data from a sensor unit that is coupled to a body of a gloveless user, wherein the gesture data is indicative of a bodily gesture of the user, wherein the bodily gesture comprises movement pertaining to at least one limb of the gloveless user. The system further includes a location determiner component that determines location of the bodily gesture with respect to a touch-sensitive display apparatus. The system also includes a display component that causes the touch-sensitive display apparatus to display an image based at least in part upon the received gesture data and the determined location of the bodily gesture with respect to the touch-sensitive display apparatus.

Abstract: A system that can automatically narrow the search space or recognition scope within an activity-centric environment based upon a current activity or set of activities is provided. In addition, the activity and context data can also be used to rank the results of the recognition or search activity. In accordance with the domain scoping, natural language processing (NLP) as well as other types of conversion and recognition systems can dynamically adjust to the scope of the activity or group of activities thereby increasing the recognition systems accuracy and usefulness. In operation, a user context, activity context, environment context and/or device profile can be employed to effectuate the scoping. As well, the system can combine context with extrinsic data, including but not limited to, calendar, profile, historical activity data, etc. in order to define the parameters for an appropriate scoping.

Abstract: A system that can identify, create, update and/or process a workflow based upon a current, past or future activity is disclosed. A ‘workflow’ can be defined as an activity flow that includes interaction with, or assignment of work to, people, devices, or services by a single individual or a group of individuals. Once a workflow is determined in accordance with the innovation, the system can inform other users or groups that are performing, or intend to perform, a similar or like activity. In establishing the workflow, the innovation can operate in an ad hoc or authored manner. As well, the system can employ a combination of either ad hoc or authored mechanisms in establishment of the workflow.

Abstract: A handwriting recognition system interprets handwritten text and produces a typed interpretation of that text. When the initial interpretation of the handwritten text is inaccurate, the handwriting recognition system alters the initial recognition by reinterpreting the handwritten text in view of a correction made by a user and constraints (e.g., derived by assumptions in user behavior). The handwriting recognition system intelligently reinterprets and renews its text recognition each time the user implements a correction. In effect, a single correction can trigger multiple adjustments to the text recognition. Therefore, with the use of a reinterpretation algorithm, the handwriting recognition system helps the user obtain the desired result in fewer correction steps.

Abstract: A system and method that facilitates and effectuates in situ search for active note taking. The system and method includes receiving gestures from a stylus and a tablet associated with the system. Upon recognizing the gesture as belonging to a set of known and recognized gestures, the system creates an embeddable object, initiates a search with terms indicated by the gesture, associates the search results with the created object and inserts the object in close proximity with the terms that instigated the search.

Abstract: Providing axonometric views of layers containing objects while preserving the visual attributes of the objects is disclosed. A group of objects, e.g., overlapping objects, is determined. Layer dimensions are calculated such that each object in the group is encompassed by a layer. Objects are placed in the layers and the layers are displayed in axonometric views. Visual cues to indicate selected layers are provided. Controls to adjust the depth of the layers and to enable moving objects in the selected layer are also provided.

Abstract: A system that can integrate activities across machines and/or devices is disclosed. The innovation can be used in an “asynchronous” manner that enables a user to move or direct a set of activities and/or tasks within an activity from one device to another. Further, the system can facilitate adapting user interface factors with respect to a particular device such that a user can “synchronously” utilize all devices for the given activities and/or tasks. In other words, the “synchronous” scenario enables a user to share activity information between devices when simultaneously utilizing multiple devices in accordance with a particular activity.

Abstract: A method for classifying brain states in electroencephalograph (EEG) signals comprising building a classifier model and classifying brain states using the classifier model is described. Brain states are determined. Labeled EEG data is collected and divided into overlapping time windows. The time dimension is removed from each time window. Features are generated by computing the base features; combining the base features to form a larger feature set; pruning the large feature set; and further pruning the feature set for a particular machine learning technique. Brain states in unlabeled EEG data are classified using the classifier model by dividing the unlabeled EEG data into overlapping time windows and removing the time dimension from each time window. Features required by the classifier model are generated. Artifacts in the labeled and unlabeled EEG data comprise cognitive artifacts and non-cognitive artifacts.

Abstract: A tournament-style gaming scenario exploration system and method for interactively exploring current and future scenarios of a tournament and associated pick'em pool. The system and method include a prediction module (including a game constraint sub-module), and a key event detection module. Embodiments of the prediction module include a binary integer that represents tournament outcomes. The prediction module generates predictions of tournament outcomes using an exhaustive or a sampling technique. The sampling technique includes random sampling, where the tournament bracket is randomly sampled, and a weighted sampling technique, which sample portions of the tournament bracket more densely than others areas. Embodiments of the game constraint sub-module allow real-world results constraints and user-supplied constraints to be imposed on the tournament outcomes.

Abstract: An interactive concept learning image search technique that allows end-users to quickly create their own rules for re-ranking images based on the image characteristics of the images. The image characteristics can include visual characteristics as well as semantic features or characteristics, or may include a combination of both. End-users can then rank or re-rank any current or future image search results according to their rule or rules. End-users provide examples of images each rule should match and examples of images the rule should reject. The technique learns the common image characteristics of the examples, and any current or future image search results can then be ranked or re-ranked according to the learned rules.

Abstract: The subject disclosure relates to a method and system for visual object categorization. The method and system include receiving human inputs including data corresponding to passive human-brain responses to visualization of images. Computer inputs are also received which include data corresponding to outputs from a computerized vision-based processing of the images. The human and computer inputs are processing so as to yield a categorization for the images as a function of the human and computer inputs.

Abstract: Displaying the relative depth of 2D image objects while preserving the visual attributes of the objects is disclosed. After an object group is determined, the members of the object group are temporarily moved away from a center location while preserving the object group members' positions relative to each other in the X-Y plane. A depth well is displayed at the center location and each object group member is connected to a ring-beam in the depth well. In response to a control action indicating a relative depth adjustment of an object group member relative to the remaining object group members, the depth of the object relative to the remaining object group members is changed. In response to a control action indicating the depth adjustment is complete, object group members are returned to their original positions in the X-Y plane with the adjusted object displayed at the object's new relative depth.