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"Memory Programs"
Models of Human Memory
Ancient storytellers kept their audience spellbound, not only because it was the only form of entertainment around, but also because they gave people an engaging way to remember past events and pass them on to new generations.
In those days, there wasn't a lot to remember. One day was almost like another. Only births, deaths, weddings and the occasional skirmish broke the monotony.
Between air travel and the Internet, the world has grown more complex. We have more choices, more information, and more things to remember. Our brains are buffeted with multitudes of events, and we can't recall important information, let alone where we left our keys.
Eric Horvitz, the research manager for Adaptive Systems and Interaction, has been researching models of memory to help us remember.
"Memory is a core aspect of intelligence that gives us an ability to review the past and anticipate the future. I've been pursuing methods and models that show promise for giving computers insights about what people will remember and forget," said Horvitz.
"Models of memory can be used in applications that help people remember-as well as to help them to search or browse through large amounts of content."
Predicting Memorable Events
Studies of episodic memory show that people use 'landmarks' to guide their recall. These memory markers include personal and public events, such as the birth of a child or 9/11 for Americans.
Horvitz and his colleagues believed that they could build a system that identified key memory landmarks by learning and predicting which events would come to serve as memorable "handles" into activities of the past.
They focused their initial efforts on events stored in users' online calendars. To build a memory model, they developed a calendar event crawler that analyzes a user's calendar.
The crawler creates a library of events and the properties associated with them. It extracts numerous properties for each event, including date, duration, subject, location, and relationships among people involved with the event. The crawler also considers the statistics of properties over time for the events in a user's life.
"We consider all that Outlook knows about events as well as other properties of events that we compute from long-term statistics and information from other sources such as organizational relationships," said Horvitz. "We can harvest a great deal of information about events, and we wanted to see what properties came out as the most predictive for people."
They found that certain patterns of properties indicate that an event is likely a memorable landmark. If a meeting invitation comes into your inbox, but you don't reply, the meeting probably isn't important to you, and therefore you probably won't consider that event a memory landmark, or perhaps not even remember the event several months later.
However, if the organizer is Bill Gates, or the location is a beach on Maui, then you'll more likely remember the event as a landmark in time-given that you don't drink one rum cola too many.
Events that recurred were unlikely to serve as useful landmarks in time. Such repetitive events tend to blur together.
From this research, they learned more about what makes events memory landmarks. They wanted to integrate these insights into easy to use applications and services that could help people remember and to more effectively find things.
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