Internet Search and Information Neighbourhoods
I’ve written and blogged on the idea of information neighbourhoods several times. Here’s the original blog post, for more just type “information neighbourhoods” into the search box in the left margin.
The basic idea is that a collection of information resources should be contextually arranged for easy use (which assumes you know the needs and regular activities of your target user community). Now the problem behind that is that a manually compiled information neighbourhood gets out of date very quickly. So neighbourhoods powered by metadata (tagging, taxonomies and other clustering data) and search (entity extraction, semantic analysis, authority and relevancy ranking) are clearly the way to go.
It looks like search is already moving in that direction, as this interview with search company Kosmix points out. Kosmix uses semantic analysis to cluster webpages in a variety of ways, and has pre-configured information neighbourhoods that essentially assemble links in ways that are very easy to use and navigate – a million times better than either the random assemblies of undifferentiated search links returned by Google, or the overly-constrained old style Yahoo subject navigation.
A good example is the RightHealth website powered by Kosmix. A high level taxonomy organises the topics in accessible ways, and my bet is that there is a more sophisticated ontology feeding the semantic analysis that pulls content into the relevant modules. Take a look.
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