Carlo Tasso

Functional and teleological knowledge in the multimodeling approach for reasoning about physical systems: a case study in diagnosis

The basic concepts of the multimodeling approach to the representation of physical systems are presented. Emphasis is placed on the exploitation of many, diverse models of a system for the execution of complex problem solving tasks, such as interpretation, diagnosis, design, simulation, etc. The considered models are based on different ontologies, representational assumptions, epistemological types, and aggregation levels. After a brief survey of the techniques adopted for representing structural and behavioral knowledge, attention is focused on function and teleology. A novel approach is proposed for defining, representing, and using these two types of knowledge which play a fundamental role both from the representation and reasoning perspectives. The fundamental claim is that while teleological knowledge concerns the specific purposes for which the system has been designed, functional knowledge is devoted to bridge the gap between such abstract purposes and the actual structure and behavior of the system, through the concepts of phenomena, processes, and functional roles. A clear definition is provided of all the various epistemological and ontological links existing between the different models. >

NLI: a robust interface for natural language person-machine communication

Abstract In this paper, a novel approach to natural language understanding, called goal oriented parsing, is presented. Such a model of comprehension is embedded in the more general frame of interpersonal communication and is applied to the person-machine interaction task. It is based on the claim that understanding imperative natural language is strongly dependent both on the goal of the speaker and on the nature of the hearer. This assumption has proved appropriate for the design of effective and robust natural language interfaces to artificial systems. This approach is supported by the development of an experimental project, called NLI, for enquiring in Italian a relational data base. NLI is to date running on a PDP 11/34 computer at the University of Udine. In this paper we illustrate the overall architecture of the system, along with the basic features of the parsing algorithm. This is based on the new concept of hierarchical parsing and is mainly directed by the semantics of the language. The role of clarification dialogue to overcome critical situations is discussed as well. The use of goal oriented parsing in dealing with full query text and anaphora is also exploited. Several meaningful examples are presented. Comparisons with related works are outlined and promising directions deserving further investigation are presented.

A shell for developing non-monotonic user modeling systems

This paper first presents a general structured framework for user modeling, which includes a set of basic user modeling purposes exploited by a user modeling system when providing a set of services to other components of an application. At a higher level of abstraction such an application may perform a generic user modeling task , which results from an appropriate combination of some basic user modeling purposes. The central aim of the paper is to present, within the proposed framework, a flexible general-purpose shell, called UMT (User Modeling Tool), which supports the development of user modeling applications. UMT features a non-monotonic approach for performing the modeling activity: more specifically, it utilizes a modeling approach called assumption-based user modeling, which exploits a truth maintenance mechanism for maintaining the consistency of the user model. The modeling task is divided into two separate activities, one devoted to user classification and user model management, and the other devoted to consistency maintenance of the model. The modeling knowledge exploited by UMT is represented by means of stereotypes and production rules. UMT is capable of identifying, at any given moment during an interaction, all the possible alternative models which adequately describe the user and are internally consistent. The choice of the most plausible one among them is then performed using an explicit programmable preference criterion. UMT is also characterized by a very well defined and simple interface with the hosting application, and by a specialized development interface which supports the developer during the construction of specific applications. This paper includes an example application in the field of information-providing systems. UMT has been developed in Common LISP.

Evaluating user interfaces to information retrieval systems: a case study on user support

Designing good user interfaces to information retrieval systems is a complex activity. The design space is large and evaluation methodologies that go beyond the classical precision and recall figures are not well established. In this paper we present an evaluation of an intelligent interface that covers also the user-system interaction and measures users satisfaction. More specifically, we describe an experiment that evaluates: (i) the added value of the semiautomatic query reformulation implemented in a prototype system; (ii) the importance of technical, terminological, and strategic supports and (iii) the best way to provide them. The interpretation of results leads to guidelines for the design of user interfaces to information retrieval systems and to some observations on the evaluation issue.

User modeling in intelligent information retrieval

Abstract The issue of exploiting user modeling techniques in the framework of cooperative interfaces to complex artificial systems has recently received increasing attention. In this paper we present the IR-NLI II system, an expert interface that allows casual users to access online information retrieval systems and encompasses user modeling capabilities. More specifically, an illustration of the user modeling subsystem is given by describing the organization of the user model proposed for the particular application area, together with its use during system operation. The techniques utilized for the construction of the model are presented as well. They are based on the use of stereotypes, which are descriptions of typical classes of users. More specifically, they include both declarative and procedural knowledge for describing the features of the class to which the stereotype is related, for assigning a user to that class, and for acquiring and validating the necessary information during system operation.

User modeling in expert man-machine interfaces: a case study in intelligent information retrieval

The requirements of a user modeling component for an expert interface are analyzed, and the main points of a proposed approach to user modeling are stated. The authors focus on a knowledge-based system, called UM-tool, devoted to creating, maintaining, and using explicit user models within an expert interface. UM-tool supports a novel approach to user modeling, which is based both on the use of stereotypes and on a dynamic reclassification scheme. The architecture of the system is described, the organization and content of its knowledge bases are illustrated, and the modeling mechanisms utilized are presented in detail. An example of the use of UM-tool in the frame of the information-retrieval-natural-language-interface (IR-NLI II) expert interface devoted to supporting end users in accessing online information retrieval services is discussed, focusing on the specific role of the user modeling component. An evaluation of the proposed approach and a critical comparison with related work are presented. Future research directions are outlined. >

Strategic help in user interfaces for information retrieval

Brajnik et alia describe their view of an effective retrieval interface, one which coaches the searcher using stored knowledge not only of database structure, but of strategic situations which are likely to occur, such as repeating failed tactics in a low return search, or failing to try relevance feedback techniques. The emphasis is on the system suggesting search strategy improvements by relating them to an analysis of work entered so far and selecting and ranking those found relevant. FIRE is an interface utilizing these techniques. It allows the user to assign documents to useful, topical and trash folders, maintains thesauri files automatically searchable on query terms, and it builds, using user entries and a rule system, a picture of the retrieval situation from which it generates suggestions.

Forward and backward reasoning in automatic abstracting

The paper is devoted to present a new approach to automatic abstracting which is supported by the development of SUSY, an experimental system currently being implemented at the University of Udine (Italy). The original contribution of the research reported is mostly focused on the role of forward and backward reasoning in the abstracting activity. In the paper the specifications and basic methodologies of SUSY are introduced, its architecture is illustrated with particular attention to the organization of the basic algorithms, and an example to support the novel approach proposed is described.

Ephemeral and Persistent Personalization in Adaptive Information Access to Scholarly Publications on the Web

We show how personalization techniques can be exploited to implement more adaptive and effective information access systems in electronic publishing. We distinguish persistent (or long term) and ephemeral (or short term) personalization, and we describe how both of them can be profitably applied in information filtering and retrieval systems used, via a specialized Web portal, by physicists in their daily job. By means of several experimental results, we demonstrate that persistent personalization is needed and useful for information filtering systems, and ephemeral personalization leads to more effective and usable information retrieval systems.

Brief paper: An expert intermediary system for interactive document retrieval

Constructing natural language interfaces to computer systems often requires achievement of advanced reasoning and expert capabilities in addition to basic natural language understanding. In this paper the above issue is tackled in the frame of an actual application concerning the design of a natural language interface for interactive document retrieval. After a short discussion of the peculiarities of this application, which requires both natural language understanding and reasoning capabilities, the general architecture and fundamental design criteria of a system presently being developed at the University of Udine are presented. The system, named IR-NLI, is aimed at allowing non-technical users to directly access through natural language the services offered by online databases. Attention is later focused on the basic functions of IR-NLI, namely understanding, dialogue and reasoning. An example of interaction with IR-NLI is fully worked out to introduce the main features of the system. Knowledge representation methods and algorithms adopted are then illustrated. Perspectives and direction for future research are also discussed.