Web of Indexes

In WWW , an index is a document like any other. An index may be built to cover a certain domain of information. For example, at CERN there is a CERN computer center document index . There is a separate functional telephone book index . Indexes may be built by the original information provider, or by a third party as a value-added service.

Indexes may point to other indexes. An index search on one index may turn up another index in the result hit list. In this case, the following algorithm seems appropriate.

Index context

Most index searches nowadays, though some look like intelligent semantically aware searches, are basically associative keyword searches. That is, a document matches a search if there is a large correlation (with or without boolean operations) between the set of words it or its abstract contains and the set of words specified in the search. Let us consider extending these searches to linked indexes.

Each index has a certain context. This may be represented by a set of keywords which may be considered to apply implicitly to everything indexed. For example, in the CERN computer center documentation index, one may imagine that everything in it will be considered as pertaining to the CERN computer center. We might represent the context by the keyword list "CERN computer center documentation physics support".

Context narrowing

Suppose we search a general physics index with the keywords "CERN NEWSLETTER". That index may contain an entry with keyword "CERN" pointing to the CERN index. Therefore, a search on the first index will turn up the CERN index. We should then search the CERN index, but looking only for the keyword "NEWSLETTER". The keyword "CERN" is discarded, as it is assumed by the new context. In this simple model, we can assume that the contextwords could be used directly as the keywords for the index itself.

A simple algorithm, then, would be for the server to discard from a search list any keywords matching the index's context -- but is this really what we want to do? Perhaps those keywords have a more refined meaning within the context. For example, if I am looking for documents about document storage schemes at CERN, I might search the index with the keyword "documents". I don't want this to be discarded because it is in the context: I am looking for documents about documents. It is understood that we are already within the context of computer center documentation, so to ask about documentation in this context implies more than that I am looking for a document.

A more refined approach would therefore be to strip from the search those keywords which were used in order to find the index. The keyword list for the entry of one index within anotherthen reflects the change in context.

Context Broadening

We have discussed here only a narrowing of context, not a broadening. One can imagine also a reference to a broader context index. In this case, perhaps one should add to the search some keywords which come from the original context but were not expressed. This would be dangerous, and people would not like it as they often feel that they are expressing their request in absolute terms even when they are not. Also, they may have been trying to escape from too restricing a context.

One should also consider a search which traces hypertext links as well as using indexes.

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Tim BL