  Chinese input methods are used to convert pinyin sequence or other Latin
encoding systems into Chinese character sentences. For more effective
pinyin-to-character conversion, typical Input Method Engines (IMEs) rely on a
predefined vocabulary that demands manually maintenance on schedule. For the
purpose of removing the inconvenient vocabulary setting, this work focuses on
automatic wordhood acquisition by fully considering that Chinese inputting is a
free human-computer interaction procedure. Instead of strictly defining words,
a loose word likelihood is introduced for measuring how likely a character
sequence can be a user-recognized word with respect to using IME. Then an
online algorithm is proposed to adjust the word likelihood or generate new
words by comparing user true choice for inputting and the algorithm prediction.
The experimental results show that the proposed solution can agilely adapt to
diverse typings and demonstrate performance approaching highly-optimized IME
with fixed vocabulary.
