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These simple parameters significantly affect broker behaviour. For example, by maximising the expertise
partition, we can achieve more value of the broker as an expert. By increasing the value of the retrieval cost
necessary for replication, we reduce the number of brokers replicating a given abstract, thus, potentially
reducing whole amount of the “expert” brokers with duplicated expertise.
All abstracts that are obtained as query results and recognised as valuable after presentation to users, are cached
locally, at least in the wide view group, if the cost of their retrieval is higher than some threshold. The LRU
(Least Recently Used) algorithm is used to update the cache. If there are many similar abstracts to a new one in
the expertise group, and the ranking scores are high enough, the new abstract is included into the expertise
group.
Adding a New Broker
A broker consists of a software and a database. The parts that differ one broker from another one are setup
parameters and the database. Setup parameters must be provided by the owner of the broker. However, to make
a new broker working, we have to supply it with knowledge of the world, which is the content of the database.
To do this, we can “transplant” a database from any working broker.
In the worst case, the donor broker is topologically far from the receiver and there is nothing common between
the corporate user profile of the owner of the donor and the owner of the receiver. This means that:
1. The database information about the retrieval costs is wrong. This leads to ineffective query routing.
2. The database is irrelevant to the local users. This leads to remote processing of the most of queries.
However, in both cases the situation improves gradually, with the broker updating its cache and, thus, adapting
to the changed conditions. To achieve better results in a shorter time, one should borrow the database from as
“close” a broker as possible. We mean “close” in topological and corporate user profile aspects.
Another way to start a new broker is to supply it with address of the closest functioning broker for default query
routing. In this case, for the first time, most of the queries will be re-routed to that one until the new broker
accumulates enough knowledge for independent functioning.
What Can What’sHot Do for Its Users
Suppose only one organisation is running a broker of this type. The broker enables people to transparently share
their expert knowledge about the availability and value of the resources, thus reducing the time and cost of
searchs for information. The communication cost of a search is reduced because many queries are resolved
locally. The broker in this case works as a very large dynamic searchable corporate hot list filled with useful
URLs which people can transparently share. People do create such hot lists at the moment, but they do it
manually, cannot search them and do not transparently share them.
Suppose that there is a deployed network of the brokers. Given that each broker can maintain information about
thousands of other brokers, the overall indexing capacity of this network is enormous. A functioning network
composes a kind of serachable space and enables people to publish their materials within this space. This is a
remarkable decentralised way of publishing where everyone can publish anything, but only the best materials
will be replicated widely and find their way to the mass consumer.
Acknowledgements
The work reported in this paper has been funded in part by the Co-operative Research Centres Program through
the Department of the Prime Minister and Cabinet of the Commonwealth Government of Australia.