Abstract: A computing system comprises, in one example, a display system, a user profile update system configured to update a user profile for a given user, a data extraction system configured to analyze a data source and to extract, from the data source, at least one work attribute associated with the given user, and a surfacing system. The surfacing system comprises a suggestion generator component configured to generate a user profile suggestion based on the at least one work attribute, and a display system controller configured to control the display system to generate a user interface display, with user input mechanisms, that displays the user profile suggestion and to detect a user interaction with the user input mechanisms. The user profile update system updates the user profile based on the detected user interaction.

Abstract: The present invention extends to methods, systems, and computer program products for understanding tables for search. Aspects of the invention include identifying a subject tuple (e.g., a subject column) for a table, detecting a tuple header (e.g., a column header) using other tables, and detecting a tuple header (e.g., a column header) using a knowledge base. Implementations can be utilized in a structured data search system (SDSS) that indexes structured information, such as, tables in a relational database or html tables extracted from web pages. The SDSS allows users to search over the structured information (tables) using different mechanisms including keyword search and data finding data.

Abstract: A method for reconstructing a super-resolution image, including: 1) reducing the resolution of an original high-resolution image to obtain an equal low-resolution image, respectively expressed as matrix forms yh and yl; 2) respectively conducting dictionary training on yl and yhl to obtain a low-resolution image dictionary Dl; 3) dividing the sparse representation coefficients ?l and ?hl into training sample coefficients ?l_train and ?hl_train and test sample coefficients ?l_test and ?hl_test; 4) constructing an L-layer deep learning network using a root-mean-square error as a cost function; 5) iteratively optimizing network parameters so as to minimize the cost function by using the low-resolution image sparse coefficient ?l_train as the input of the deep learning network; 6) inputting the low-resolution image sparse coefficient ?l_testas the test portion into the trained deep learning network in 5), outputting to obtain a predicted difference image sparse coefficient {circumflex over (?)}hl_test, computing

Abstract: The present invention extends to methods, systems, and computer program products for understanding tables for search. Aspects of the invention include identifying a subject column for a table, detecting a column header using other tables, and detecting a column header using a knowledge base. Implementations can be utilized in a structured data search system (SDSS) that indexes structured information, such as, tables in a relational database or html tables extracted from web pages. The SDSS allows users to search over the structured information (tables) using different mechanisms including keyword search and data finding data.

Abstract: A system, method or computer readable storage device to derive a taxonomy from keywords is described herein. A domain-dependent taxonomy from a set of keywords may be automatically derived by leveraging both a general knowledgebase and keyword search. For example, concepts may be deduced with the technique of conceptualization, and context information may be extracted from a search engine. Then, the taxonomy may be constructed using a tree algorithm.

Abstract: An ultra-high temperature (UHT) rigidity seal ball valve that includes an upper cover, a valve cover, a valve body, a valve rod and a ball body. The valve seat is arranged in the valve body; the valve rod penetrates the upper cover and the valve cover sequentially and connects to the ball body; a sealing element is arranged between the upper cover and the valve rod and between the valve cover and the valve rod; the ball body includes a medium channel; a hermetically-sealed cooling cavity encircles the outside of the medium channel of the ball body; a through hole allowing cooling liquid to pass through to the cooling cavity is formed in the valve rod. An accommodating cavity is arranged in the ball body; the through communicates with the accommodating cavity, so that cooling liquid can be introduced to a product when the valve operates at an ultra-high temperature.

Abstract: An ultra-high temperature (UHT) rigidity seal ball valve that includes an upper cover, a valve cover, a valve body, a valve rod and a ball body. The valve seat is arranged in the valve body; the valve rod penetrates the upper cover and the valve cover sequentially and connects to the ball body; a sealing element is arranged between the upper cover and the valve rod and between the valve cover and the valve rod; the ball body includes a medium channel; a hermetically-sealed cooling cavity encircles the outside of the medium channel of the ball body; a through hole allowing cooling liquid to pass through to the cooling cavity is formed in the valve rod. An accommodating cavity is arranged in the ball body; the through communicates with the accommodating cavity, so that cooling liquid can be introduced to a product when the valve operates at an ultra-high temperature.

Abstract: The present invention extends to methods, systems, and computer program products for understanding tables for search. Aspects of the invention include identifying a subject column for a table, detecting a column header using other tables, and detecting a column header using a knowledge base. Implementations can be utilized in a structured data search system (SDSS) that indexes structured information, such as, tables in a relational database or html tables extracted from web pages. The SDSS allows users to search over the structured information (tables) using different mechanisms including keyword search and data finding data.

Abstract: A system, method or computer readable storage device to derive a taxonomy from keywords is described herein. A domain-dependent taxonomy from a set of keywords may be automatically derived by leveraging both a general knowledgebase and keyword search. For example, concepts may be deduced with the technique of conceptualization, and context information may be extracted from a search engine. Then, the taxonomy may be constructed using a tree algorithm.