Microsoft Technology Licensing, LLC

Xi Chen

Matthew Robert Scott

Weipeng Liu

Huihua Hou

Weijiang Xu

Hao Wei

Chiwei Che

Byron Huntley Changuion

Rongfeng Lai

Yonghong Shi

Mu Li

Chi-Ho Li

An input method editor (IME) provides a distributed platform architecture that enables associating multiple applications with the IME to provide extended functionalities. The presentations of the applications, such as skins, may be different from each other and that of the IME. The applications may be represented in a manifest file that is human-readable and editable. The IME collects multiple parameters relating to a user input into a host application including a query input by the user and a scenario of the host application, and selects one or more applications to provide candidates based on a score or ranking of the applications under the collected multiple parameters. Machine-learning may be used to improve the score or ranking. The candidates may include text candidates, rich candidates, and informative candidates.

Input method editor application platform

An input method editor (IME) described herein couples scenarios of the input of the user with specific network services to offer more relevant and richer candidates for higher input productivity. Data relating to a computer application in which the input candidates are to be input and/or context relating to a user-submitted query is collected and analyzed to determine a scenario. The input candidates may include text candidates and rich candidates. The IME may select a scenario-tuned and type specific engine to identify the text candidates and/or rich candidates. The scenario-tuned text candidate engines leverage scenario-tuned language models and lexicons, and the scenario-tuned rich candidate engines leverage scenario-relevant web services, such as image, mapping, and video search, when available and appropriate.

Scenario-adaptive input method editor

Some implementations provide techniques and arrangements for semantic lexicon based processing, such as in an input method editor. In some instances, a semantic label may be received that is to be defined for a semantic lexicon and at least a first term may be identified as a positive or negative example of the semantic label. In response, some examples may label at least a second term in the semantic lexicon with the semantic label based at least in part on the identification of the first term as a positive or negative example of the semantic label.

Semantic lexicon-based input method editor

Some examples include generating a personal language model based on linguistic characteristics of one or more files stored at one or more locations in a file system. Further, some implementations include predicting and presenting a non-Latin character string based at least in part on the personal language model, such as in response to receiving a Latin character string via an input method editor interface.

Personal language model for input method editor

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Tianjin, China

Xi Chen