The FindMe approach to assisted browsing

TLDR

The explosion of online information has created opportunities for data use but also highlighted the challenge of isolating useful content and understanding large, multidimensional information spaces. This article illustrates these techniques with examples of working FindMe systems and describes their similarities and differences. FindMe systems combine instance‑based browsing—retrieval around critiqued examples—with knowledge‑based heuristics for locating relevant information. FindMe tour guides help users navigate information spaces, providing useful information and insights into the space’s structure, and assist in selecting items such as cars, movies, restaurants, stereos, or apartments on the Web.

Abstract

While the explosion of online information has introduced new opportunities for finding and using electronic data, it has also underscored the problem of isolating useful information and making sense of large, multidimensional information spaces. In response to this problem, we have developed an approach to building data tour guides, called FindMe systems. These programs know enough about an information space to help users navigate through it, making sure they not only come away with useful information but also insights into the structure of the information space itself. In these systems, we have combined the idea of instance-based browsing, which involves structuring retrieval around the critiquing of previously retrieved examples, and retrieval strategies, or knowledge-based heuristics for finding relevant information. This article illustrates these techniques with examples of working FindMe systems, and describes the similarities and differences between them. FindMe tour guides help users to select the perfect car, movie, restaurant, stereo or apartment on the World Wide Web.