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Publications

  1. Giunchiglia, Fausto; Ghidini, Chiara,
    Local Models Semantics, or Contextual Reasoning = Locality + Compatibility,
    Proceedings of the Sixth International Conference on Principles of Knowledge Representation and Reasoning,
    Morgan Kaufmann,
    1998
    , pp. 282-
    289
    , (Sixth International Conference on Principles of Knowledge Representation and Reasoning (KR'98),
    Trento, Italy,
    1998)
  2. Chiara Ghidini,
    A Semantics for Contextual Reasoning: Theory and Two Relevant Applications,
    Since McCarthy`s Turing Award speech, in 1971, the notion of context has been used in Artificial Intelligence to localize reasoning, in the sense that intelligent agents reasoning depends on the situation agents are embedded in, and on their cognitive state. A typical example is McCarthy`s above theory, in which, depending on context, the `same` theory, describing a blocks world, can be represented in two different ways with a different degree of generality. The emphasis on the role of context in localizing reasoning does not mean that there is no relation between reasoning performed in different contexts. In many applications of contexts, e.g. reasoning about beliefs, reasoning about viewpoints, integration of heterogeneous information, and multiagent systems, reasoning may involve many interacting contexts. Therefore a certain form of compatibility must exist between facts described in different contexts. This thesis aims at defining a semantics for contextual reasoning, called Local Models Semantics, that formalizes the role of context in localizing reasoning and the relations (compatibilities) among different contexts. Additionally we use tis semantics to formalize two relevant applications, that is, reasoning about beliefs and the integration of heterogeneous information in a federated database. By developing the theory of Local Models Semantics we pursue two objectives. First we aim to illustrate the intuitions underlying the use of context in reasoning. In addition we define a formal semantics for contextual reasoning which formalizes these intuitions. These objectives are accomplished by giving the basic definitions of model, satisfiability, and logical consequence. By applying Local Models Semantics to reasoning about beliefs we intend to provide evidence that our semantics provides enough modularity and flexibility to formalize agents with various introspective reasoning capabilities. Finally, by applying Local Models Semantics to the integration of information coming from heterogeneous databases, we intend to show that a precise formal semantics of a federation of databases can be defined by considering each database in the federation as a context and interactions between different databases as relations between contexts,
    1998
  3. Luciano Serafini; Chiara Ghidini,
    Context Based Semantics for Federated Databases,
    International and Interdisciplinary Conference on Modeling and Using Context [Context-97],
    1997
    , pp. 33-
    45
    , (International and Interdisciplinary Conference on Modeling and Using Context [Context-97],
    Rio de Janeiro, Brasil,
    1997)
  4. Luciano Serafini; Chiara Ghidini,
    Local Models Semantics for Information Integration,
    AAAI Fall symposium on Context in Knowledge Representation (KR) and Natural Language (NL),
    AAAI,
    1997
    , (AAAI Fall symposium on Context in Knowledge Representation (KR) and Natural Language (NL),
    Cambridge, Massachusetts,
    08/11/1997 - 10/11/1997)
  5. Massimo Benerecetti; Paolo Bouquet; Chiara Ghidini,
    A Multi Context Approach to Belief Report,
    AAAI Fall symposium on Context in Knowledge Representation (KR) and Natural Language (NL),
    AAAI,
    1997
    , (AAAI Fall symposium on Context in Knowledge Representation (KR) and Natural Language (NL),
    Cambridge, Massachusetts,
    08/11/1997 - 10/11/1997)
  6. Luciano Serafini; Chiara Ghidini,
    Formalizing and Reasoning about Constraints in Federated Databases,
    Due to the increasing necessity and availability of information from different sources, information integration is becoming one of the challenging issues in artificial intelligence and computer science. A successful methodology for information integration is based on Federated Databases (FDB). However, differently form databases (DBs) a completely satisfactory formal treatment of FDB is still missing. The goal of this paper is to fill this gap. Our basic intuition is that an FDB can be formalized by considering each DB of the federation as a context. We argue that this perspective is a promising one, as some of the relevant problems in the area of information integration, such as semantic heterogeneity, can be successfully solved using contexts. In the paper we provide a formal notion of FDB schema, a semantics for such a schema, called Local Models Semantics for FDBs, and a deduction system which formalizes the logical consequence of Local Models Semantics. We show by means of examples that our formalization overcomes the drawbacks of the previous approaches,
    1997
  7. Chiara Ghidini; Luciano Serafini,
    Foundation of Federated Databases, I: A Model Theoretic Perspective,
    Due to the increasing necessity and availability of information from different sources, information integration is becoming one of the challenging issues in artificial intelligence and computer science. A successful methodology for information integration is based on Federated Databases. However, differently form databases, a completely satisfactory formal treatment of federated databases is still missing. The goal of this paper is to fill this gap by providing a model theoretic semantics, called ‘Local Models Semantics for federated databases’. Our basic intuition is that a federated database can be formalized by representing each database as a set of local models. We argue that this perspective is a promising one, as many relevant problems in information integration, such as semantic heterogeneity, interschema dependencies, query distribution, local control over data and processing, and transparency, can be successfully solved by local model semantics. In the paper we provide a formal notion of federated database schema, a semantics for such a schema, and a definition of logical consequence for this semantics. We show its adequacy by means of three motivating examples,
    1997
  8. Luciano Serafini; Chiara Ghidini,
    Local Semantics for Federated Databases,
    In many applications which need for a large amount of information, knowledge is partitioned and represented in a set of databases (DB) integrated in a federated database (FDB). A FDB is a collection of distributed, partial, redundant, and partially autonomous DBs. Distribution, redundancy, partiality and autonomy generate many problems in the management of a FDB. The most important are semantic etherogenity, update propagation, inter-schema dependencies, and query distribution which need for a formal treatment. Several approaches have been proposed in the past. However these formalisms are inadequate as they partially represent some of the aspects, but they fail to represent all of them. The goal of this paper is to develop a formal semantics called local semantics, for FDB, which explicitly represents distributed, redundant, partial, autonomous DBs. We substantiate the above adequancy claim by formalizing three motivating examples which involves all these aspects,
    1996
  9. Chiara Ghidini,
    Semantiche a Modelli Locali per Logiche MultiContestuali,
    1994

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