T9 predictive text in Windows Forms
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Hey - we're looking at trying to implement a T9-based predictive text capability (like on your cell phone/PDA) into our Windows forms application (this is running on a standard Windows/embedded environment, NOT on a smart phone). Has anyone seen or worked with anything like this in the past? Cheers, Chris
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Hey - we're looking at trying to implement a T9-based predictive text capability (like on your cell phone/PDA) into our Windows forms application (this is running on a standard Windows/embedded environment, NOT on a smart phone). Has anyone seen or worked with anything like this in the past? Cheers, Chris
For that you need to do following. 1. Maintain one dictionary which will serve as base for auto suggestion. 2. Bind that dictionary with your textbox. 3. Track keypress event of your textbox and suggest world if it is starting from the character user enters. That's All. HTH
Jinal Desai - LIVE Experience is mother of sage....
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For that you need to do following. 1. Maintain one dictionary which will serve as base for auto suggestion. 2. Bind that dictionary with your textbox. 3. Track keypress event of your textbox and suggest world if it is starting from the character user enters. That's All. HTH
Jinal Desai - LIVE Experience is mother of sage....
Thanks for the reply. However, I'm not sure if you're following one of the key points I was trying to accomplish - T9. I'm not working by standard letter entry, but rather by T9 entry (or the newer XT9). In the very least this would involve adding the equivalent T9 values for each word in the dictionary, but it still wouldn't account for word usage/popularity. Obviously there are ways that this can be coded completely from scratch, but I wanted to first see if anyone was doing something similar using an already establish method, API, etc. Thanks again.
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Thanks for the reply. However, I'm not sure if you're following one of the key points I was trying to accomplish - T9. I'm not working by standard letter entry, but rather by T9 entry (or the newer XT9). In the very least this would involve adding the equivalent T9 values for each word in the dictionary, but it still wouldn't account for word usage/popularity. Obviously there are ways that this can be coded completely from scratch, but I wanted to first see if anyone was doing something similar using an already establish method, API, etc. Thanks again.
Yes definitely possible, though probably not entirely in .NET, and don't think there are API beside the standard Win32 API, and you got to code most of the libraries. You'll need a light and efficient database for the dictionary, an algorithm to retrieve the words fast, an algorithm to account for the most recent used words, adding and removing words from the dictionary. You'll need some way to hook the keypress, and sending the character or control characters (backspace, etc) to the control. Did a Palm version for a friend's company for the keyboard, they did the windows mobile version using C++. Though without much capital, the product is currently sort of dead. :( http://www.osnews.com/story/15389/Review-TenGO-2.0-and-TenGO-Thumb[^]
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Hey - we're looking at trying to implement a T9-based predictive text capability (like on your cell phone/PDA) into our Windows forms application (this is running on a standard Windows/embedded environment, NOT on a smart phone). Has anyone seen or worked with anything like this in the past? Cheers, Chris
G-Tek wrote:
Has anyone seen or worked with anything like this in the past?
Not T9, but been playing with something similar. Kinda started with a Wiktionary-download, gives you a decent dictionary. Once that was in place, started fetching websites to do a statistical analysis. Read a few sites in a loop (of the correct target-audience) and mark how often a word follows the previous word. Thus resulted in a crash of my machine :) Filtered out all noise-words for the analysis, as there's a lot of words that might follow the word "this". The remark on the target-audience would be important because "this" often has a different meaning on the CodeProject-site than in normal conversation. ..and that's when I stopped playing with it, my harddisk isn't that large. You wouldn't need the complete resultset to give decent options as a prediction; only the top 5000 or so. Still, sounds like a lot of work, and the method that I described here is probably one of the less efficient ways to do it.
I are Troll :suss: