Microsoft Technology Licensing, LLC

Weipeng Liu

Matthew Robert Scott

Xi Chen

Huihua Hou

Weijiang Xu

Robert Lovejoy Goodwin

Christopher Clayton McConnell

Hao Wei

Shahin Shayandeh

Chiwei Che

Byron Huntley Changuion

Rongfeng Lai

Yonghong Shi

Ming Zhou

Yingnong Dang

Jin Shi

Mu Li

Kun Jing

Song Ge

Sadi Khan

Chi-Ho Li

Gong Cheng

Dongmei Zhang

Technologies are described herein for denormalizing data instances. Schemas for data instances are embedded with annotations indicating how the denormalization is to be performed. Based on the annotations, one or more sub per object indexes ('sub POIs') can be generated for each data instance and stored. The sub POIs can include a target sub POI containing data from the data instance, and at least one source sub POI containing data from another data instance, if the data instance depends on the other data instance. Data instance updates can be performed by identifying sub POIs that are related to the updated data instance in storage, and updating the related sub POIs according to the update to the data instance. The sub POIs can be sent to an indexing engine to generate an index for a search engine to facilitate searches on the data instances.

Efficient denormalization of data instances

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) configured to provide language assistance across a plurality of applications is disclosed. In one example, the IME is adapted for use by English-as-a-second-language (ESL) users. In a specific example, language assistance may be provided by first detecting a need to suggest a substitute word to a user who is typing within an application. The detection may be based on a probability that a current word is in error. If a need is detected, a suggestion may be obtained for the word, such as from a cloud linguistic service or from a local lexicon and language-model, if network connectivity is poor. Once obtained, the suggestion may be displayed to the user in a non-intrusive manner by user interface element(s). Interaction with the user allows the user to accept or reject the suggestion, and perform other functions, such as relocating user interface elements utilized by the display.

Input method editor providing language assistance

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

The customization of an application user interface with a skin package based on context data that includes the emotional states of a user may strengthen the emotional attachment for the application by the user. The customization includes determining an emotional state of a user that is inputting content into an application. A skin package for the user interface of the application is selected based on the emotional state of the user. The selected skin package is further applied to the user interface of the application.

Sentiment aware user interface customization

Growing community of inventors

Beijing, China

Weipeng Liu