Abstract: The present method includes: transforming a gray matrix of a natural scene image into a local contrast matrix, and performing a binary division to the obtained local contrast matrix using an Otsu method, thereby obtaining a binary matrix; performing a connected domain analysis to the binary matrix, eliminating non-character connected domains to obtain character connected domains; performing a detection of elements of a special structure of a formula to the character connected domains using a correlation coefficient method, and separately annotating all the detected elements of the special structure: dividing rows of the binary matrix by means of horizontal projection; recognizing each character connected domain by means of a convolutional neural network; defining an output sequence, and outputting the results of recognition in a corresponding sequence according to a typesetting format of LaTeX.

Abstract: A method for structural analysis and recognition of a handwritten mathematical formula in a natural scene image, including: transforming a gray matrix of a natural scene image into a local contrast matrix, and performing a binary division to the obtained local contrast matrix using an Otsu method, thereby obtaining a binary matrix; performing a connected domain analysis to the binary matrix, eliminating non-character connected domains to obtain character connected domains; performing a detection of elements of a special structure of a formula to the character connected domains using a correlation coefficient method, and separately annotating all the detected elements of the special structure: dividing rows of the binary matrix by means of horizontal projection; recognizing each character connected domain by means of a convolutional neural network; defining an output sequence, and outputting the results of recognition in a corresponding sequence according to a typesetting format of latex.

Abstract: A technique for generating a social circle for a user of a social network is provided. A personalized circle-user graph (PCUG) model may be constructed based on friends of the user and social circles joined by the friends. At least partly based on connections between the friends and social circles in the PCUG model, the social circles may be ranked. A candidate social circle may be generated based on rankings of the social circles.

Abstract: Systems, methods, and computer-readable and executable instructions are provided for categorizing a concept. Categorizing a concept can include selecting a target concept with a number of surrounding textual contexts. Categorizing a concept can also include determining a number of candidate categories for the target concept based on the number of surrounding textual contexts. Categorizing a concept can also include selecting a predefined number of articles, each with a desired relatedness to the number of candidate categories. Furthermore, categorizing a concept can include calculating a relatedness score for each of the number of candidate categories based on a relatedness with the number of articles.

Abstract: Facilitating information retrieval and improving similarity score computations among objects, via a compactor component that interacts with a layered memory structure. Data structures (e.g., tuples) that are associated with objects can be compacted into a condensed format, via employing a layered memory structure. The system further includes a sorting component that is operatively coupled with the “compactor component”, to reduce memory space that is required to store and retrieve similarity scores related to various objects.