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MENTOR: Internet Search Advisor and Information Retrieval System
Introduction
A. A. Tsinakos and K. G. Margaritis
Department of Informatics
University of Macedonia
54006 Thessaloniki
GREECE
Tel : +30-31- 891 891
E-mail: tsinakos/kmarg@kirki.it.uom.gr
Internet provides access to hundreds of gigabytes of information through a variety of wide-area filing,
information retrieval, publishing and library access systems. This rapidly growing data volume and diversity in
Internet has created significant problems related to the efficiency and accuracy of the information retrieval. To
make effective use of this wealth of information, user needs means to locate information. Additionally,
information in existing Internet repositories is heterogeneous, inconsistent and sometimes incomplete
[Bowman and Danzig and Manber and Schwartz 1994]. This fact increases the difficulty of the above
mentioned problem. In the past few years, a number of such resource discovery tools have been created such
as: 1) Internet Browsing and Exploring systems, such as Gopher, Hytelnet, Global Network Navigator, 2)
Subject - Oriented Search systems, such as WWW, Virtual Library, Yahoo, USENET Frequently Asked
Questions Archive, 3) Word - Oriented Search systems, such as Lycos, Web Crawler, Knowbot, Archie, WAIS
and have gained wide popular acceptance in the Internet.
Further models originally developed for Artificial Intelligence research, have been applied to Information
Retrieval leading to the development and evaluation of intelligent retrieval models for text documents, such as
those found in bibliographic databases. These retrieval models specify strategies for evaluating documents with
respect to a given query, typically resulting in a ranked output. Hypertext researchers, on the other hand have
emphasized flexible organizations of multimedia "nodes" through connection made with user-specified links
and interfaces that facilitate browsing in this network of links. A number of approaches to the integration of
query-based retrieval strategies and browsing in hypertext networks have been proposed. The I3R system
[Croft and Thompson 1987] and the medical handbook system described by Frisse, for example, use query
based retrieval strategies to form a ranked list of candidate "starting points" for hypertext browsing.
Finally a number of probabilistic retrieval models for hypertext have been proposed [Frisse and Cousins 1989]
[Savoy and Desbois, 1991]. These models view hypertext links as specifying important dependencies between
hypertext nodes. The aim of the retrieval strategies based on these models are to improve the effectiveness of
retrieval and to provide better starting points for browsing [Croft and Turtle, 1993].
In this paper we present a propose-and-revise system which automates the construction of a search strategy
(in a specific domain) for Internet based information retrieval, in order to help novice or non novice Internet
users to access and retrieve information using a variety of Internet search engines and information resources.
Overview description of MENTOR system
MENTOR system can be analysed in five levels 1) User level: The system can be accessed by one or multiple
users and this is the starting point of user - system interaction. 2) Data Input-Output level: The front - end
interface of the system, implemented in HTML, in which the user is allowed as first step, to insert his
selections in a dialogue box and additionally to receive the results both of the proposed search strategy and the
Internet search. 3) MENTOR's Advisor level: At this level the system implements and combines user inputs
with the expert suggestions (using the pre-stored Librarian, Internet and Domain expert knowledge) in order to
report the preferable search strategy, that is suggested to be followed, back to the user. A detailed description
of this level is given in the following section. 4) Query Transformation level: This level is responsible for the