## Predictive Text

*February 16, 2009 at 1:50 am* *felipecol* *
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How many text messages do you send per day? If you are like most young adults, the answer is probably a number between 2 and… I don’t know 10?. Well, In 2007 the average cell phone user sent 188 text messages per month, which equals roughly 2,256 texts a year or 6 per day. But I am sure that by now those numbers have gone way up. Maybe one of the reasons that text messaging has become so popular is that technologies such as predictive text make this technology so easy to use.

Predictive text is an input technology that reduces the number of key strokes necessary to enter a word, thus simplifying the process of writing text messages or emails. There are several types of predictive text technologies such as T9, iTap, eZiText and Word Logic. But how does it work? Well let me tell you that it was almost impossible to find a good simplified explanation, however I did find out that it takes some complicated mathematical equations that use several variables to compute possible word outcomes.

Just take a look at this link and you will see what I am talking about! Predictive Text (You don’t have to read this whole article just notice the math involved)

Basically how this works is that a dictionary is stored in a computing system, and then a program is created to allow that as the user presses the number buttons on the cell phone that triggers a mathematical algorithm that searches the dictionary for a list of possible words and offers the most probable (common) choice.

Similar technologies recently became available by search engines such as Google, Youtube, and Wikipedia. In these cases, predictive search helps you find what you are looking for before you even finish entering the whole phrase. I am sure most of you have already seen this, but in the picture shows that all I needed to type was “Illinois st” for Google to predict that I was searching “Illinois State University”, based partly on probabilities.

Thanks, and remember to take the blackboard assessment for this post at: https://blackboard.ilstu.edu/webct/entryPageIns.dowebct

Edison.

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