International Business Machines Corporation

Xi'an Jiaotong University

Yang Yang

Juan Wu

Long Fan

Ye Fan

Qi Mao

Jing James Xu

Jia Zhong Wu

Wen Pei Yu

Chong Liu

Jinghuai Gao

Zhiguo Wang

Zhaoqi Gao

Yumin Chen

Qiannan Wang

Zhen Li

A computer-implemented method, system and computer program product for automatically drawing infographics. Variables of a dataset are received from a computing device that were selected by the user of the computing device. For those selected variables that are associated with a data model, a procedure to draw infographics for variables assigned or not assigned the role of a target using the data model associated with each of the variables assigned or not assigned the role of target, respectively, is implemented. Alternatively, if the selected variables are not associated with a data model, then such variables are assigned a level of measurement as well as assigned the role of input. Such assignments become the data model which, along with the metadata (e.g., values of the variable) obtained by parsing the original data, are used to implement the procedure to draw infographics for variables not assigned the role of a target.

Automatically drawing infographics for statistical data based on a data model

Using a set of menu to key process mappings, historical menu usage data for an application is aggregated into aggregated key process usage data. A set of key process association rules, each comprising a consequent key process given a particular antecedent key process, is generated. From the set of key process association rules and a set of ranked menus by frequency of usage within each key process, a set of model menu recommendations is generated. According to an application usage history, a menu frequency ratio, and a confidence value of a modelled next menu, the set of menu recommendations is scored. A scored menu recommendation having a rank below a threshold rank is pruned from a set of menu items of the application ranked according to their scores. The pruned set of scored menu recommendations is presented for selection instead of the set of menu items.

Behavior based menu item recommendation and pruning

An automatic seismic facies identification method based on combination of Self-Attention mechanism and U-shape network architecture, including: obtaining and preprocessing post-stack seismic data to construct a sample training and validation dataset; building an encoder through an overlapped patch merging module with down-sampling function and a self-attention transformer module with global modeling function; building a decoder through a patch expanding module with linear upsampling function, the self-attention transformer module, and a skip connection module with multilayer feature fusion function; building a seismic facies identification model using the encoder, the decoder, and a Hypercolumn module, where the seismic facies identification model includes a Hypercolumns-U-Segformer (HUSeg); and building a hybrid loss function; iteratively training the seismic facies identification model with a training and validation set; and inputting test data into a trained identification model to obtain seismic facies corresponding to the test data.

Automatic seismic facies identification method based on combination of self-attention mechanism and u-shape network architecture

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Xi'an, China

Yang Yang