Giorgio Terracina

The INFOMIX system for advanced integration of incomplete and inconsistent data

The task of an information integration system is to combine data residing at different sources, providing the user with a unified view of them, called global schema. Users formulate queries over the global schema, and the system suitably queries the sources, providing an answer to the user, who is not obliged to have any information about the sources. Recent developments in IT such as the expansion of the Internet and the World Wide Web, have made available to users a huge number of information sources, generally autonomous, heterogeneous and widely distributed: as a consequence, information integration has emerged as a crucial issue in many application domains, e.g., distributed databases, cooperative information systems, data warehousing, or on-demand computing. Recent estimates view information integration to be a

Recommendation of similar users, resources and social networks in a Social Internetworking Scenario

10 Billion market by 2006 [14].

Experimenting with recursive queries in database and logic programming systems

In this paper we propose an approach to recommend to a user similar users, resources and social networks in a Social Internetworking Scenario. Our approach presents some interesting novelties with respect to the existing ones. First of all, it operates on a Social Internetworking context and not on a single social network. Moreover, it considers not only explicit relationships among users but also the implicit ones, connecting users on the basis of shared interests and behavior; the latter is derived from the analysis of user actions in the considered Social Internetworking Scenario. In addition, it considers the presence of possible semantic anomalies involving the description of available users, resources and social networks. Finally, it takes into account not only the local information regarding involved users, resources and social networks but also the global one, i.e., the information spread all over the considered Social Internetworking Scenario.

The third answer set programming competition: preliminary report of the system competition track

This article considers the problem of reasoning on massive amounts of (possibly distributed) data. Presently, existing proposals show some limitations: (i) the quantity of data that can be handled contemporarily is limited, because reasoning is generally carried out in main-memory; (ii) the interaction with external (and independent) Database Management Systems is not trivial and, in several cases, not allowed at all; and (iii) the efficiency of present implementations is still not sufficient for their utilization in complex reasoning tasks involving massive amounts of data. This article provides a contribution in this setting; it presents a new system, called DLVDB, which aims to solve these problems. Moreover, it reports the results of a thorough experimental analysis we have carried out for comparing our system with several state-of-the-art systems (both logic and databases) on some classical deductive problems; the other tested systems are LDL++, XSB, Smodels, and three top-level commercial Database Management Systems. DLVDB significantly outperforms even the commercial database systems on recursive queries.

Uniform techniques for deriving similarities of objects and subschemes in heterogeneous databases

Answer Set Programming is a well-established paradigm of declarative programming in close relationship with other declarative formalisms such as SAT Modulo Theories, Constraint Handling Rules, FO(.), PDDL and many others. Since its first informal editions, ASP systems are compared in the nowadays customary ASP Competition. The Third ASP Competition, as the sequel to the ASP Competitions Series held at the University of Potsdam in Germany (2006-2007) and at the University of Leuven in Belgium in 2009, took place at the University of Calabria (Italy) in the first half of 2011. Participants competed on a selected collection of declarative specifications of benchmark problems, taken from a variety of domains as well as real world applications, and instances thereof. The Competition ran on two tracks: the Model & Solve Competition, held on an open problem encoding, on an open language basis, and open to any kind of system based on a declarative specification paradigm; and the System Competition, held on the basis of fixed, public problem encodings, written in a standard ASP language. This paper briefly discuss the format and rationale of the System competition track, and preliminarily reports its results.

DIKE: a system supporting the semi-automatic construction of cooperative information systems from heterogeneous databases

The availability of automatic tools for inferring semantics of database schemes is useful to solve several database design problems such as that of obtaining cooperative information systems or data warehouses from large sets of data sources. In this context, a main problem is to single out similarities or dissimilarities among scheme objects (interscheme properties). This paper presents graph-based techniques for a uniform derivation of interscheme properties including synonymies, homonymies, type conflicts, and subscheme similarities. These techniques are characterized by a common core: the computation of maximum weight matchings on some bipartite weighted graphs derived using a suitable metrics to measure semantic closeness of objects. The techniques have been implemented in a system prototype. Several experiments conducted with it, and (in part) accounted for in the paper, confirmed the effectiveness of our approach.

The disjunctive datalog system DLV

In this paper we present DIKE, a system supporting the semi‐automatic construction of cooperative information systems from heterogeneous databases. The input of DIKE consists of the set of databases to belong to the cooperative system. First, DIKE constructs a data repository representing a structured, integrated and consistent description of the information stored in the input databases. The data repository thus constructed is then used as the core structure of a mediator‐like module supporting the user‐friendly integrated access to available data resources. The core of DIKE is the extraction and exploitation of the inter‐schema knowledge (in the form of inter‐schema properties) relative to the involved database schemas. Copyright

A unified graph-based framework for deriving nominal interscheme properties, type conflicts and object cluster similarities

DLV is one of the most successful and widely used answer set programming (ASP) systems. It supports a powerful language extending Disjunctive Datalog with many expressive constructs, including aggregates, strong and weak constraints, functions, lists, and sets. The system provides database connectivity offering a simple way for powerful reasoning on top of relational databases. In this paper, we provide an ample overview of the DLV system. We illustrate its input language and give indications on how to use it for representing knowledge. We also provide a panorama on the system architecture and the main optimizations it incorporates. We then focus on DLVDB, an extension of the basic system which allows for tight coupling with traditional database systems. Finally, we report on a number industrial applications which rely on DLV.

An XML-Based Multiagent System for Supporting Online Recruitment Services

The availability of automatic tools for inferring semantics from database schemes is very relevant in designing large cooperative information system applications involving many information sources. Deriving semantics from existing data sources exploits properties of objects belonging to different input schemes (interscheme properties), such as synonymies, homonymies, type conflicts, and subscheme similarities. The paper gives a contribution in this context by proposing a collection of graph based techniques for a uniform derivation of all interscheme properties. All techniques are characterized by a common core consisting of the computation of a maximum weight matching on suitable bipartite graphs. The computation of the maximum weight matching is based on a suitable metrics which is used to measure object semantic similarities. A running example is provided to illustrate the approach.

A graph-based approach for extracting terminological properties of elements of XML documents

In this paper, we propose an Extensible Markup Language (XML)-based multiagent recommender system for supporting online recruitment services. Our system is characterized by the following features: 1) it handles user profiles for personalizing the job search over the Internet; 2) it is based on the intelligent agent technology; and 3) it uses XML for guaranteeing a light, versatile, and standard mechanism for information representation, storing, and exchange. This paper discusses the basic features of the proposed system, presents the results of an experimental study we have carried out for evaluating its performance, and makes a comparison between the proposed system and other e-recruitment systems already presented in the past.