Predictive Text Input in a Mobile Shopping Assistant: Methods and Interface Design (IUI-2009)

Predictive Text Input in a Mobile Shopping Assistant: Methods and Interface Design (IUI-2009)

By: Peter Peltonen, Petri Saarikko, Petteri Nurmi, Andreas Forsblom (may have forgotten one or 2)

Summary:
Everyone goes grocery shopping on a regular basis and many people use grocery lists to keep track of their information on what items they need to purchase. Even though many people acknowledge the importance of shopping lists little research has been done into the creation and management of them. This paper discusses a predictive text input technique that uses association rules and item frequencies to integrate a shopping assistant into a web based mobile device. There are two types of shopping assistants (those for shopping in malls and those for shopping in individual shops). The ones for malls are more concerned for getting the user to the store while the ones for individual shops focus on item level location. This device was limited to grocery items which sampled products and then mapped them into a shopping list. This list of items they searched through took out any unit sizes or things that dealt with brand names and simply referred to the base item (8oz pkg of kraft macaroni = macaroni). They then calculate the Term Frequency-Inverse Document Frequency and score for each word in the product name and return the lowest TF-IDF score when entering a new item. If the rules do not trigger a text prediction then they use a frequent item for prediction.

Users were given 2 different versions of the interface. One that had predictive text and one that didn’t. After the users completed a list with their device they filled out a satisfaction survey. The predictive text input functionality increased the user’s input speed. On average, the increase was around 5 words per minute. It also reduced error rates by about 80% and increased user satisfaction.

Discussion:
I thought the ideas behind this topic were interesting and that the paper was well written. I like the idea of a shopping assistant that would keep track of my grocery list because I know there are a lot of times were I go to the store to get items that are related. Like when making spaghetti you go to the store for butter, noodles, spaghetti sauce, mushrooms, beef etc. I think this is a very useful point of research that could be extended into many other aspects of every day life.