Papers in PDF format

All relevant information and links to other useful sites have to be included in order to make our system stand
out from already existing ones and to avoid that the user has to search the WWW for missing information. It is
also important that our information service appears at the right places, with a meaningful abstract, for people
using a WWW search engine.
The System and the Proposed Solution
The web-site will ultimately contain all the information our users need, as well as links to related web pages. In
order to facilitate navigation within the web-site a search engine, based on intelligent agent technology, assists
the user in finding relevant pages.
For example, Alan Miller, Personnel Manager for Allied Breweries, specifies his preferences to be recruitment,
training and testing & assessment upon registering with the service. When he does a search on computer
software the same suggestions will come up as for other users, but the order will be different: software related
to recruitment, training and testing & assessment will be put first.
According to our user study a significant number of prospective users prefer other types of searches to keyword
search and we will probably get many people ‘browsing’ rather than searching for something in particular. We
therefore asked our sample to propose structures for topics of their interest in order to be able to build our site
in accordance with the mental model of our average user.
Implementation
When the user first enters the site, she has the opportunity to register. This is done to benefit from the
personalised agent. If she chooses to do so a graphical user interface comes up, prompting her to enter her
details and preferences. The interface is programmed in Java and looks similar to many HTML forms. A new
record is created and the information entered by the user is stored in the engine’s knowledge base. The user
can decide on a name under which the agent will ‘recognise’ her. In order to use the search engine, the user
has to enter her name, which allows the search engine access to her details and preferences. Then she can enter
up to three keywords of the information she is looking for into the keyword field of the search engine interface.
A database stores information about each page: its URL, and up to 8 keywords that describe the contents of the
page. The keyword(s) entered by the user are first compared to a list of synonyms of all keywords in the
database and replaced with the term chosen for the database. For example, the user might have entered the
words jobs and education. The corresponding terms in the database are recruitment and training respectively.
Each term, however, has a list of synonyms (e.g. recruitment: jobs, employment, vacancies, …) and if the
user’s keyword is found therein, it is replaced by the database word (e.g. jobs is replaced with recruitment)
before the search engine searches the page database.
The user’s keywords are compared to the keywords of the pages and three lists are created: The first with all
those pages which have three of the user’s keywords among their keywords, the second with those that have
two keywords in common and a third list with pages that only have one match. The lists are then sorted
according to known user details and preferences. For example, someone looking for ‘employment law’ and
‘solicitor’ will get all pages with that description presented before the pages that have only one of those
keywords linked to them. Furthermore, those pages with solicitors in the same city or county will be put first.
Equally, when a user who specified ‘training’ as one of their main interests runs a search on ‘computers’ and
‘software’ she will get pages related to training software put before pages with lists of dealers or software
developers. Once the lists are sorted they are displayed to the user: the one with three matches first, followed
by the one with two matches and the one with one match last. The user can then go to the suggested pages by
clicking on their highlighted URL.
Future work