Dario Lucarella

A fuzzy object-oriented data model for managing vague and uncertain information†

In this paper, a fuzzy Object‐Oriented Data model (FOOD) is defined based on the extension of a Graph‐based Object model (D. Lucarella and A. Zanzi “A graph‐oriented data model,” in Database and Expert Systems Applications, R. Wagner and H. Toma, Eds., Springer‐Verlag, Berlin, 1996, pp. 197–206), in order to manage both crisp and imperfect information. These capabilities are requisites of many current applications dealing with data of different nature and with complex interrelationships. The model is based on a visual paradigm which supports both the representation of the data semantics and the direct browsing of the information. In the extended model both the database scheme and instances are represented as directed labeled graphs in which the fuzzy and uncertain information has its own representation. ©1999 John Wiley & Sons, Inc.

FIRST: fuzzy information retrieval SysTem

This paper discusses modelling, design and imple mentation issues for a knowledge-based information retrieval system Both the domain knowledge representation and the inference mechanism are based upon a fuzzy set theoretical framework The system manages natural language queries and returns a ranked set of relevant documents, computing for each of them a degree of support depending on multiple sources of evidence. In the following, after a brief remark about the need for modelling the inherent imprecision associated with the retrieval process, a model based on fuzzy reasoning is proposed. Then the architecture is presented of FIRST, a prototype system which is intended as an experimental test-bed for the applica tion of intelligent techniques in order to improve the effective ness of information retrieval systems Finally, we discuss im plementation details with reference to the retrieval component and related strategies that have been developed to reduce the impact of using imprecise knowledge upon the computational efficiency of the system.

A document retrieval system based on nearest neighbour searching

Document filing and retrieval systems can be designed using advanced techniques resulting from recent research in information retneval. In this paper, a document retneval system is presented, based upon the vector processing model. The system employs an automatic indexing procedure with a weighting scheme to reflect term importance. Documents are stored using an in verted file organization. Natural language quenes are sup ported with a retrieval strategy based on best match techniques and relevance feedback. The emphasis is on nearest neighbour searching to locate documents closest to a given query. That means, after having defined a sirrularitv function, the identification of those docu ments in the collection which exhibit a higher degree of re semblance to the query. The problem is introduced with reference to a straightfor ward search procedure that returns the nearest neighbour set manipulating the inverted file entnes. Then. an improved al gorithm is presented which optimizes both the number of documents to be evaluated and the number of inverted lists to be inspected.

A fuzzy object oriented data model

The increasing complexity of real applications in the field of multimedia information systems requires the enhancement of modelling capabilities of object oriented data models (OODMs) in order to deal with imprecise and uncertain data. Some fuzzy extensions of the OODMs have been proposed in the literature, in which imprecision and uncertainty are managed at the level of object attributes and relations. What is still lacking is a unifying and systematic formalization of these extensions. In this contribution, starting from an existing graph-based-object model, the authors propose a fuzzy object oriented data (FOOD) model for the management of imprecise data.<<ETX>>

A visual retrieval environment for hypermedia information systems

We present a graph-based object model that may be used as a uniform framework for direct manipulation of multimedia information. After an introduction motivating the need for abstraction and structuring mechanisms in hypermedia systems, we introduce the data model and the notion of perspective, a form of data abstraction that acts as a user interface to the system, providing control over the visibility of the objects and their properties. A perspective is defined to include an intension and an extension. The intension is defined in terms of a pattern, a subgraph of the schema graph, and the extension is the set of pattern-matching instances. Perspectives, as well as database schema and instances, are graph structures that can be manipulated in various ways. The resulting uniform approach is well suited to a visual interface. A visual interface for complex information systems provides high semantic power, thus exploiting the semantic expressibility of the underlying data model, while maintaining ease of interaction with the system. In this way, we reach the goal of decreasing cognitive load on the user, with the additional advantage of always maintaining the same interaction style. We present a visual retrieval environment that effectively combines filtering, browsing, and navigation to provide an integrated view of the retrieval problem. Design and implementation issues are outlined for MORE (Multimedia Object Retrieval Environment), a prototype system relying on the proposed model. The focus is on the main user interface functionalities, and actual interaction sessions are presented including schema creation, information loading, and information retrieval.

Information retrieval from hypertext: an approach using plausible inference

Abstract This paper approaches the problem of information retrieval from hypertext. In this context, the retrieval process is regarded as a process of inference that can be carried out either by the user exploring the hypertext network, browsing, or by having the system exploit the hypertext network as a knowledge base, searching. In the following, a comprehensive model is proposed taking into account both of the perspectives, and combining effectively browsing and querying into a unified framework. Hypertext nodes are regarded as facts, links as rules, and the connected hypertext structure as an inference network that can be used to prove the query inferentially. Next, design and implementation issues are discussed concerning a prototype system developed to evaluate the proposed approach in terms of retrieval effectiveness and search efficiency.

MORE: Multimedia Object Retrieval Environment

We present a graph-based object model that may be used as a uniform framework for direct manipulation of multimedia information. After an introduction motivating tbe need for abstraction and structuring mechanisms in hypermedia systems, we introduce the data model and the notion of perspective, a form of data abstraction that acts as a user interface to the system, providing control over the visibility of the objects and their properties. A perspective is defined to include an intension and an extension, The intension is defined in terms of a pattern, a subgraph of the schema graph, and the extension is the set of pattern-matching instances. Perspectives, as well as database schema and instances, are graph structures that can be manipulated in various ways. The resulting uniform approach is well suited to a visual interface. A visual interface for complex information systems provides high semantic power, thus exploiting the semantic expressibility of the underlying data model, while maintaining ease of interaction with the system. In this way, we reach the goal of decreasing cognitive load on the user, with the additional advantage of always maintaining the same interaction style, We present a visual retrieval environment that effectively combines filtering, browsing, and navigation to provide an integrated view of the retrieval problem. Design and implementation issues are outlined for MORE (.Multimedia Object Retrieval Environment), a prototype system relying on tbe proposed model, The focus is on the main user interface functionalities, and actual interaction sessions are presented including schema creation, information loading, and information retrieval.

Multi-perspective Navigation of Movies

Abstract Digital libraries of video are rapidly growing in size and availability through digital networks of computers. The explosion of digital unstructure information, such as video, traveling through the network raises the need for tools that allow video information structuring and “intelligent” access to sequences. In this paper we present a novel video database system, which has been expressly designed to support structured storage of movies. A semiotic formalization for movie logical organization is here introduced and exploited to derive the conceptual schema of an object-oriented movie database. This structure is expressly tailored to enable queries on film technical features and on semantic contents as well, thus allowing feature fusion and access from multiple perspectives. A novel visual interaction scheme is implemented that allows users to formulate queries as filtering operations, that enable focussing on the interesting part of information, while skipping the rest. Formalization of the operators of “perspective” and “filtering” is thereby supplied. Retrieval of stored sequences by iconic motion example is also implemented for accessing sequences by contents. Examples are supplied of interaction with the database and of expressive power of visual query language.

Information retrieval based on fuzzy reasoning

Abstract This paper discusses modelling, design and implementation issues for a knowledge-based information retrieval system. The system manages natural languages queries and returns a ranked set of relevant documents computing for each of them a degree of support depending on multiple sources of evidence. In our approach, the retrieval process is regarded as the problem of determining an implication relationship between a document and a query and assessing the plausibility of the implication. In the following, after a brief remark about the need for modeling the inherent imprecision associated with the retrieval process, a model based on fuzzy reasoning is proposed. Then the architecture is presented of a prototype system which has been implemented to evaluate the improvement in the overall retrieval effectiveness. Finally, we discuss implementation details with reference to search strategies that have been developed to reduce the impact of using imprecise knowledge upon the computational efficiency of the system.

The Fuzzy Object Oriented Database Management System

In this paper we present a prototypal implementation of the Fuzzy Object Oriented Data model1. FOOD has been defined for representing data characterized either by imprecision or vagueness and uncertainty. The present implementation extend the O2 system so as to allow the representation and instantiation of vague attribute values and uncertain and strengthened relations.