International Business Machines Corporation

Vagner F D Santana

Marco A S Netto

Carlos Henrique Cardonha

Andrea Britto Mattos Lima

Priscilla Barreira Avegliano

Rodrigo Laiola Guimaraes

Marcia Ito

Content of the material the user is consuming is identified. Physiological pattern generated by the user while consuming the content is captured via at a sensor device. Responsive to detecting that the physiological pattern represents an outlier, a term in the content is determined for which additional information is to be provided. The term may be determined from the content based on user knowledge, frequency of the term appearing in previous content consumed by the user and popularity of the term. A search query is executed with the determined term. Result of the search query may be filtered based on the user's knowledge. The filtered result and at least one of the previous content containing the term the user has previously consumed is presented.

Triggering personalized search queries based on physiological and behavioral patterns

Providing knowledge representation of material content being consumed by a user combines the user's current behavioral data and data from external sources such as internet web sites and social media network. Visual representations of entities and their relationships in the content being consumed by the user are created while the user is consuming content, and displayed via a graphical user interface.

Visualization and augmentation of human knowledge construction during material consumption

The present disclosure describes systems and methods for identifying products that are implicitly published in an image, e.g., where there is no identifying text or comments that identify the brand of the product. A product entity may be identified based on comments posted in response to the posting of the image. An analysis of the image may be performed based on the identified product entity to find items or products of a type of the identified product entity in the image. A product detected in the image may be compared to a database of products of the type of product entity to determine which product was posted in the image.

Processing image using narrowed search space based on textual context to detect items in the image

An online learning system selects content for a learning session and opens a user interface to start the learning session on a plurality of devices. A mode of instruction is selected for the learning session. An activity to perform associated with the content is presented. Performance of the activity is monitored and a performance metric and/or a heterogeneity metric associated with a key performance indicator for the activity performed is generated. Responsive to determining that the performance metric and/or a heterogeneity metric is outside of the target range, the mode of instruction may be switched automatically.

Learning systems and automatic transitioning between learning systems

A user interaction with a computer device is monitored, the user interaction comprising at least user consuming material via the computer device. Content of the material the user is consuming is identified. Physiological pattern generated by the user while consuming the content is captured via at a sensor device. Responsive to detecting that the physiological pattern represents an outlier, a term in the content is determined for which additional information is to be provided. The term may be determined from the content based on user knowledge, frequency of the term appearing in previous content consumed by the user and popularity of the term. A search query is executed with the determined term. Result of the search query may be filtered based on the user's knowledge. The filtered result and at least one of the previous content containing the term the user has previously consumed is presented.

An automated feedback may be provided while data is entered in an electronic form. Input entered into an input field of a form fillable window provided on a user interface display screen may be detected. A quality measure associated with the input as entered into the form fillable window may be determined. The quality measure is determined based on a quality needed for an analytics process of an application for which the input is being entered. A graphical indication representing the quality measure on the user interface display screen may be presented.

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Sao Paulo, Brazil

Vagner F D Santana