Chapter 2
Adaptive Web Sites Challenges And Approaches
Challenges:
Our challenge while dealing with adaptive websites then is this: how can we build a web site which improves itself over time in response to user interactions with the site? This challenge poses a number of difficult but not impossible questions:
• What kinds of generalizations can we draw from user access patterns and what kinds of changes could we make?
Suppose we maintain a web site containing information about various automobiles, organized by manufacturer. We observe that visitors who look at the Ford Windstar minivan page also tend to look at the Dodge Caravan and Mazda MPV minivan pages. We might therefore create a new page for minivans, which cuts …show more content…
This site contains schedules, announcements, assignments, and other information important to the hundreds of students who take the course every quarter. Enough information is available that important documents can be hard to _nd or entirely lost in the clutter. Imagine, however, if the site were able to determine what was important and make that information easiest to _nd. Important pages would be available from the site 's front page. Important links would appear at the top of the page or be highlighted. Timely information would be emphasized, and obsolete information would be quietly moved out of the way. There are several factors that make this challenge both appropriate and timely for the AI community. First, the growing popularity and complexity of the web underscores the importance of the challenge. Second, virtually all existing web sites are not adaptive, yet data to support the learning process is readily available in web server logs. Clearly, here is an opportunity for
AI! Finally, a number of disconnected projects in machine learning [Armstrong et al., 1995], data mining, knowledge representation, plan recognition [Kautz, 1987; Pollack, 1990], and user modeling [Fink et al., 1996] have begun to explore aspects of the problem. Framing …show more content…
Many advances in artificial intelligence, both practical and theoretical, have come about in response to such task-oriented approaches. The quest to build a better chess-playing computer, for example, has led to many advances in search techniques (e.g., [Anantharaman et al., 1990]). The autonomous land vehicle project at CMU [Thorpe, 1990] has resulted in not only a highway-cruising vehicle but also breakthroughs in vision, robotics, and neural networks. The quest to build autonomous software agents has similarly led to both practical and theoretical advances. For example, the Internet Softbot project has yielded both deployed softbots and advances in planning, knowledge representation, and machine learning [Etzioni,
Adaptive Web Sites Challenges And Approaches
Challenges:
Our challenge while dealing with adaptive websites then is this: how can we build a web site which improves itself over time in response to user interactions with the site? This challenge poses a number of difficult but not impossible questions:
• What kinds of generalizations can we draw from user access patterns and what kinds of changes could we make?
Suppose we maintain a web site containing information about various automobiles, organized by manufacturer. We observe that visitors who look at the Ford Windstar minivan page also tend to look at the Dodge Caravan and Mazda MPV minivan pages. We might therefore create a new page for minivans, which cuts …show more content…
This site contains schedules, announcements, assignments, and other information important to the hundreds of students who take the course every quarter. Enough information is available that important documents can be hard to _nd or entirely lost in the clutter. Imagine, however, if the site were able to determine what was important and make that information easiest to _nd. Important pages would be available from the site 's front page. Important links would appear at the top of the page or be highlighted. Timely information would be emphasized, and obsolete information would be quietly moved out of the way. There are several factors that make this challenge both appropriate and timely for the AI community. First, the growing popularity and complexity of the web underscores the importance of the challenge. Second, virtually all existing web sites are not adaptive, yet data to support the learning process is readily available in web server logs. Clearly, here is an opportunity for
AI! Finally, a number of disconnected projects in machine learning [Armstrong et al., 1995], data mining, knowledge representation, plan recognition [Kautz, 1987; Pollack, 1990], and user modeling [Fink et al., 1996] have begun to explore aspects of the problem. Framing …show more content…
Many advances in artificial intelligence, both practical and theoretical, have come about in response to such task-oriented approaches. The quest to build a better chess-playing computer, for example, has led to many advances in search techniques (e.g., [Anantharaman et al., 1990]). The autonomous land vehicle project at CMU [Thorpe, 1990] has resulted in not only a highway-cruising vehicle but also breakthroughs in vision, robotics, and neural networks. The quest to build autonomous software agents has similarly led to both practical and theoretical advances. For example, the Internet Softbot project has yielded both deployed softbots and advances in planning, knowledge representation, and machine learning [Etzioni,