A two-level hypertext retrieval model for legal data

This paper introduces an associative information retrieval model based on the two-level architecture proposed in [Agosti et al, 1989a] and[Agostiet al, 1990], andan experimental prototype developed in order to validate the model in a personal computing environment. In the fiist part of the paper, related work and motivations are presented. In the second pert, the model, entitled EXPLICIT, is introduced. EXPLICIT is basedon a two-level architecture which holds the two main parts of the informative resource managed by an information retrieval tool: the collection of documents and the indexing term structure. Theterm structure is managed as a schema of concepts which can be used by the final user as a frame of reference in the query formulation process. llemodel supports theconcurrent use of different schemas of concepts to satisfy information needs of different categories of users. Inthethird part of the paper, the main characteristics of the experimental prototype, named HyperLaw, are presented. 1. ASSOCIATIVE INFORMATION RETRIEVAL AND MOTIVATIONS OF THE WORK Associative information retrieval methods are all those retrieval methods which have been proposed and experimented since 1975 [Doyle, 1975] in order to expand query formulation by adding to an initial query some new terms related to the Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republieh, requiree a fee and/or epecific permission. @ 1991 ACM O-89791 . 448 -l/91 /0009 /0316 . $5050 terms of the initial query, and similarly expanding the retrieved document set using terms related to the already used terms [Salton & Buckley, 1988]. [Salton & Buckley, 1988] contains an up-to-date situation in designing and usage of associative information retrieval methods and shows that the difficulty encountered in applying associative retrieval methods still resides in the identification of related terms and documents which would improve retrieval operations. Concerning the currently available information retrieval systems, the most common situation is that of the user who is unable to actively interact with the indexing term structure used by the system. That is, the user is able to see a single indexing term or a list of indexing terms used in a document informative content representation, but often he cannot, at the moment of formulation of the query, effectively grasp the structure of the different indexing terms related to an indexing term of interest. A facility of this kind, if available, can prove very useful, but it is not sufficient to really inform the user of the structural organisation of the indexing terms; in fact this facility is normally available only in a non-integrated fashion and the user needs to know an indexing term beforehand in order to begin wandering through the semantic structure. With the above-mentioned research and implementation considerations in mind, we started the work reported in this paper with the following underlying motivations: to give the final user the possibility to actively browse through the indexing term structure in order to acquire a proper understanding of the semantic context in which the _ of each term has been defined by the indexers, to allow the user to see those documents related to possibly