Microsoft Technology Licensing, LLC

Beijing Bytedance Network Technology Co., Ltd.

Simon Cheng Liu

Kenichi Morimoto

Jason Michael Bower

Rui Li

Peter Gregory Davis

Cong Chen

Daryn Elliot Robbins

Kenji Furuuchi

Chet Laughlin

Chaoran Li

Honghui Sun

Heng Ma

Xianghao Guo

The present disclosure relates to a method, a device and a system for computer game difficulty assessment. The method comprises: recording game data by a data collector in a process of simulating game playing by operating a computer game through an API (Application Programming Interface) of the computer game using an agent algorithm; measuring a goal attainment difficulty of the computer game at this timing according to goal completion degrees of a plurality of goals corresponding to all attempts at each decision-making timing in the recorded game data; measuring a strategy space-related difficulty of the computer game at this timing according to goal completion degrees of a plurality of goals corresponding to all actions at each decision-making timing in the recorded game data; assessing difficulty of the computer game based on a goal attainment difficulty and a strategy space-related difficulty at each timing.

Method, device and system for game difficulty assessment

Word predictions in a message are selected or prioritized based on the recipient of the message and a previous location of use by a user. An input history is created based on messages sent to the recipient from the user at a particular location (e.g., global positioning system coordinates). As the user composes subsequent messages, a current location of the user is determined. Word predictions are performed based on a comparison of the current location to the previous locations, and based on the recipient(s). In further embodiments, location-aware spell-check functionality is provided for the messages.

Contact-specific and location-aware lexicon prediction

Context-based word prediction is provided. A software application utilizes words contained in an application document to provide context-based word prediction in the same or a related document. The software application creates an application defined data source and populates the data source with words occurring in a document. When the same or a related document is being edited via an input method, for example, typing, speech recognition, electronic handwriting, etc., a prediction engine presents candidate words from the application defined data source that match current text input, and the user may choose from the presented candidate words for automatic population into the document being edited. Information from the application defined data source may be transferred between computing devices, for example, between a mobile computing device and a desktop (non-mobile) computing device.

Context based word prediction

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Beijing, China

Simon Cheng Liu