Knowledge Organisation


Kim H. Veltman

New Approaches to Searching, Teaching, Repairing, Advertising and Selling using SUMS (System for Universal Media Searching)

Unpublished, Toronto, 1996.

1. Introduction
2. Manual Criteria
3. Semi-Manual Searching
4. Semi-Automatic Searching
5. Agent
6. Teaching and Learning
7. Training, Repair and Re-Engineering
8. Advertising and Sales
9. Static Knowledge and Dynamic Information
10. New Philosophy of Knowledge
11. Conclusions.

1. Introduction

Browsers have become one of the buzzwords of the Internet. The most elementary versions such as Mosaic and Netscape, required that one type in the precise address where one wished to go. A next stage entailed methods such as Yahoo or Lycos which arranged long lists on a given topic. Search engines such as Opentext effectively searched for all occurences of a term on-line. While this produced a great wealth of hits, it made no distinction between different contexts of a word, with the result that many or sometimes even the majority of the references proved to be of no serious interest. All of the above methods are philosophically equivalent because they assume that searching is merely a question of brawn rather than brain; that a better search engine is bigger, faster and gets more hits.

SUMS begins from a very different premise: quality is more important than quantity. Indeed if there is too much noise in the information one receives then quantity can obscure and even undermine quality. How can we find what we really want and not just that which has the same words as that which we want? This applies not only to the initial web surfing when we first find something, but also to how we organize things such that we can find them back more easily thereafter. Indeed the most basic version of SUMS focusses on organizing what we find.

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