In most current systems, a large authoring effort is required to insert links into documents. Very little work has been done in the area of automatic link construction - links based on the semantic analysis of the underlying text. Such a feature requires considerable amount of analysis and the incorporation of an Artificial Intelligence engine.
In an effort towards automatic linking of hypertext nodes, Bernstein proposed a "link apprentice", a program that can examine a draft hypertext and create appropriate links. This can be done by establishing links based on the semantic analysis of the underlying text. Since these "clever" apprentices are intrinsically difficult to construct (they not only need precision but also accuracy and recall), he suggested a "shallow apprentice" - a system which discovers links through superficial textual analysis (of statistical and lexical properties) without analyzing meaning [Bernstein, 1990].
The shallow apprentice uses the Bloom filter method of text searching. Each hypertext page (node) has a Bloom filter hash table where each word is hashed. These hash tables are used to define a similarity between two hypertext pages by taking the normalized dot product of their hash tables. The apprentice will search the entire document checking for similarity to the page upon which the hypertext author is currently working. It will then retrieve the twenty pages that appear to be most similar to the current page.
The hypertext author can also construct hypertext paths or tours by choosing an interesting starting point and requesting the apprentice to construct a path through related material. However, the path may not be in logical order since the apprentice does not check for semantics.