Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Dario Lucarella

dblp:58/3401 · DBLP profile ↗
← Back
5ranked-venue papers
3as first author
0since 2021 · last 1999
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 5 · 3 first-authorArtificial intelligence and machine learning · 3 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Information retrieval · 91% Data models and query languages · 9%

Topics — the 2 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › document retrieval › structured document retrieval
hypertext retrieval
0.011996
A Visual Retrieval Environment for Hypermedia Information Systems · ACM Trans. Inf. Syst. 1996
Information retrieval
multimedia analysis and retrieval
0.011996
A Visual Retrieval Environment for Hypermedia Information Systems · ACM Trans. Inf. Syst. 1996

Methods — techniques the papers use, named apart from their topics

perspective-based data abstraction · 0.0pattern matching · 0.0
YearPublicationVenuePosition
1999 A fuzzy object-oriented data model for managing vague and uncertain information
abstract
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.
Gloria Bordogna, Gabriella Pasi, Dario Lucarella
Int. J. Intell. Syst.3
1996 A Graph-Oriented Data Model
Dario Lucarella, Antonella Zanzi
DEXA1
1996 A Visual Retrieval Environment for Hypermedia Information Systems
abstract
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.
Dario Lucarella, Antonella Zanzi
ACM Trans. Inf. Syst.1
1993 Information Retrieval Based on Fuzzy Reasoning
Giovanni V. Guardalben, Dario Lucarella
Data Knowl. Eng.2
1993 Information Retrieval from Hypertext: An Approach Using Plausible Inference
Dario Lucarella, Antonella Zanzi
Inf. Process. Manag.1