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The ability of providing and relating temporal representations at different ‘grain levels’ of the same reality is an important research theme in computer science and a major requirement for many applications, including formal specification and verification, temporal databases, data mining, problem solving, and natural language understanding. In particular, the addition of a granularity dimension to a temporal logic makes it possible to specify in a concise way reactive systems whose behaviour can be naturally modeled with respect to a (possibly infinite) set of differently-grained temporal domains. Suitable extensions of the monadic second-order theory of $k$ successors have been proposed in the literature to capture the notion of time granularity. In this paper, we provide the monadic second-order theories of downward unbounded layered structures, which are infinitely refinable structures consisting of a coarsest domain and an infinite number of finer and finer domains, and of upward unbounded layered structures, which consist of a finest domain and an infinite number of coarser and coarser domains, with expressively complete and elementarily decidable temporal logic counterparts. We obtain such a result in two steps. First, we define a new class of combined automata, called temporalized automata, which can be proved to be the automata-theoretic counterpart of temporalized logics, and show that relevant properties, such as closure under Boolean operations, decidability, and expressive equivalence with respect to temporal logics, transfer from component automata to temporalized ones. Then, we exploit the correspondence between temporalized logics and automata to reduce the task of finding the temporal logic counterparts of the given theories of time granularity to the easier one of finding temporalized automata counterparts of them.
This book begins and ends in information retrieval, but travels through a route constructed in an abstract way. In particular it goes through some of the most interesting and important models for information retrieval, a vector space model, a probabilistic model and a logical model, and shows how these three and possibly others can be described and represented in Hilbert space. The reasoning that occurs within each one of these models is formulated algebraically and can be shown to depend essentially on the geometry of the information space. The geometry can be seen as a ‘language’ for expressing the different models of information retrieval.
The approach taken is to structure these developments firmly in terms of the mathematics of Hilbert spaces and linear operators. This is of course the approach used in quantum mechanics. It is remarkable that the application of Hilbert space mathematics to information retrieval is very similar to its application to quantum mechanics. A document in IR can be represented as a vector in Hilbert space, and an observable such as ‘relevance’ or ‘aboutness’ can be represented by a Hermitian operator. However, this is emphatically not a book about quantum mechanics but about using the same language, the mathematical language of quantum mechanics, for the description of information retrieval. It turns out to be very convenient that quantum mechanics provides a ready-made interpretation of this language.
‘Let no man enter here who is ignorant of geometry’
Plato
In the previous chapters we have introduced set-theoretic, logical and algebraic notions, all of which can be used profitably in IR. We now wish to broaden the discussion somewhat and attempt to introduce a language and a notation for handling these disparate notions within a single space, viz. Hilbert space (Simmons, 1963), thereby constructing a probability measure on that space via its geometry. At first glance this appears to be a difficult task, but if we consider that much IR research has been modelled in finite vector spaces (Salton, 1968) with an inner product, many of our intuitions for that can be transferred to the discussion based on Hilbert spaces. One major reason for adopting the more abstract point of view is that we wish to present a ‘language’ for describing and computing objects, whether text, image or speech, in a general way before considering any particular implementation.
The language introduced uses a small set of operators and functions, and the notation will be the Dirac notation (Dirac, 1958). Although at first sight the Dirac notation strikes one as confusing and indeed awkward for learning about linear algebra, its use in calculating or computing simple relationships in Hilbert space is unparalleled. Its great virtues are that any calculation is simple, the meaning is transparent, and many of the ‘housekeeping’ rules are automatically taken care of. We will demonstrate these virtues as we progress.
Security protocols stipulate how the remote principals of a computer network should interact in order to obtain specific security goals. The crucial goals of confidentiality and authentication may be achieved in various forms, each of different strength. Using soft (rather than crisp) constraints, we develop a uniform formal notion for the two goals. They are no longer formalised as mere yes/no properties as in the existing literature, but gain an extra parameter, the security level. For example, different messages can enjoy different levels of confidentiality, or a principal can achieve different levels of authentication with different principals. The goals are formalised within a general framework for protocol analysis that is amenable to mechanisation by model checking. Following the application of the framework to analysing the asymmetric Needham-Schroeder protocol (Bella and Bistarelli 2001; Bella and Bistarelli 2002), we have recently discovered a new attack on that protocol as a form of retaliation by principals who have been attacked previously. Having commented on that attack, we then demonstrate the framework on a bigger, largely deployed protocol consisting of three phases, Kerberos.
The overall goal of this paper is to investigate the theoretical foundations of algorithmic verification techniques for first order linear logic specifications. The fragment of linear logic we consider in this paper is based on the linear logic programming language called LO (Andreoli and Pareschi, 1990) enriched with universally quantified goal formulas. Although LO was originally introduced as a theoretical foundation for extensions of logic programming languages, it can also be viewed as a very general language to specify a wide range of infinite-state concurrent systems (Andreoli, 1992; Cervesato, 1995). Our approach is based on the relation between backward reachability and provability highlighted in our previous work on propositional LO programs (Bozzano et al., 2002). Following this line of research, we define here a general framework for the bottom-up. evaluation of first order linear logic specifications. The evaluation procedure is based on an effective fixpoint operator working on a symbolic representation of infinite collections of first order linear logic formulas. The theory of well quasi-orderings Abdulla et al., 1996; Finkel and Schnoebelen, 2001) can be used to provide sufficient conditions for the termination of the evaluation of non trivial fragments of first order linear logic.
This book is about underlying ideas and theory. It is about a way of looking, and it is about a formal language that can be used to describe the objects and processes in Information Retrieval. It is not about yet another model for IR, although perhaps some will want to find such an interpretation in it.
Why do we need another way of looking at things? There are some good reasons. Firstly, although there are several IR models, for example vector space, probabilistic, logical to name the most important, they cannot be discussed within a single framework. This book, The Geometry of Information Retrieval (GIR), is a first attempt to construct a unifying framework. Secondly, although many of us pay lip-service to the conceptual depth of some of the fundamental notions in IR such as relevance, we rarely analyse these notions formally to any bedrock. This is not because we are lazy, it is rather because our theoretical tools have made it very difficult to do so. What follows will, it is hoped, aid such formal analysis. And thirdly, there is a need to support the formal specification or expression of IR processes so that we can formally reason about them. For example, we need to be able to lay down mathematical constructs that will direct us in the design of some new algorithms for IR. This is especially important if we wish to extend the boundaries of current research.
In this paper we present a notion of expansion of a term in the lambda-calculus which transforms terms into linear terms. This transformation replaces each occurrence of a variable in the original term by a fresh variable taking into account non-trivial implications in the structure of the term caused by these simple replacements. We prove that the class of terms which can be expanded is the same of terms typable in an Intersection Type System, i.e. the strongly normalizable terms. We then show that expansion is preserved by weak-head reduction, the reduction considered by functional programming languages.
Haskell today provides good support not only for a functional programming style, but also for an imperative one. Elements of imperative programming are needed in applications such as web servers, or to provide efficient implementations of well-known algorithms, such as many graph algorithms. However, one element of imperative programming, the global variable, is surprisingly hard to emulate in Haskell. We discuss several existing methods, none of which is really satisfactory, and finally propose a new approach based on implicit parameters. This approach is simple, safe, and efficient, although it does reveal weaknesses in Haskell's present type system.
In this paper, we describe two techniques for the efficient, modularized implementation of a large class of algorithms. We illustrate these techniques using several examples, including efficient generic unification algorithms that use reference cells to encode substitutions, and highly modular language implementations. We chose these examples to illustrate the following important techniques that we believe many functional programmers would find useful. First, defining recursive data types by splitting them into two levels: a structure defining level, and a recursive knot-tying level. Second, the use of rank-2 polymorphism inside Haskell's record types to implement a kind of type-parameterized modules. Finally, we explore techniques that allow us to combine already existing recursive Haskell data-types with the highly modular style of programming proposed here.