Papers in PDF format

the worst case, we can make a rough judgement on the value of resource transparently for users based on how
often it has been retrieved by users.
We feel it would be a good idea to also include at least “Could not get” check box and “Submit” button into
result forms of other search engines. This way would enable the search engines to clean their indexes.
How It Works
Each broker consists of a database and software that performs following functions:
1. Maintain, index and search the local cache of the abstracts..
2. Process incoming queries locally and send results back to clients.
3. If a query can not be processed locally or the user is not satisfied with the results of local processing, make
decisions on routing the query to other sources of meta-information.
4. Make decisions on caching (replication) of remote query results (which are sets of abstracts) locally.
5. Publish (make available for queries) the abstracts of local and/or authorised users.
6. Periodically recommend the most popular abstracts to other brokers that might be interested in getting a copy
of the abstract for replication.
7. Make decisions on caching locally abstracts recommended by other brokers.
Data
The way we build the broker’s cache is similar to what happens in the process of human learning. We (human
beens) collect relatively small bits of knowledge about every possible topic we face in our life, from road traffic
rules to rumours about crimes. The more it is interesting for us, the more often we use this knowledge, the
longer we remember it. We also have knowledge (often vague) about possible sources where we can get more
information on a given topic, if necessary. This part of memory is our knowledge cache and knowledge map.
Most of people are experts in a narrow area. If they are recognised as the experts, their expertise is used by
other people directly or indirectly. If one is a known expert in some area, we ask them for information on this
area and sometime we suggest a new information for their judgement or if we want this information to be
known to other people through them or just to contribute to their expertise.
The broker’s database contains three groups of abstracts.
- Abstracts which are popular among the local users and form a corporate user profile. We call this group the
“wide view group”. It is knowledge cache and knowledge map of the broker.
- A specialised group of abstracts on some topic, prevailing in the wide view group. We call this group the
“expertise” group.
- Abstracts that are published by local users. We call this group the “local group”.
Additional information is stored for each abstract. This includes expiry date, date last used (for resource
retrieval or query routing), source broker, popularity rating, cost of retrieval, user profiles.
It makes sense to store abstracts of the wide view group because the information that is interesting for one user
within the organisation, is very likely to be interesting for the others. Second, this group of abstracts forms a
knowledge map of the outside world of information sources. It contains a dynamic set of abstracts covering a
wide range of topics. This information is used to choose the best sources for given search topic.
Storage of the expertise group makes sense because we need to concentrate knowledge of a topic as much as
possible to reduce need for query distribution. In other words, we have to achieve specialisation of a broker in
some topic. If we do this, only a few brokers need to be searched for a particular topic, or a combination of
topics, instead of the millions of brokers as in the case of dispersed information.