460 research outputs found
Space-contained conflict revision, for geographic information
Using qualitative reasoning with geographic information, contrarily, for
instance, with robotics, looks not only fastidious (i.e.: encoding knowledge
Propositional Logics PL), but appears to be computational complex, and not
tractable at all, most of the time. However, knowledge fusion or revision, is a
common operation performed when users merge several different data sets in a
unique decision making process, without much support. Introducing logics would
be a great improvement, and we propose in this paper, means for deciding -a
priori- if one application can benefit from a complete revision, under only the
assumption of a conjecture that we name the "containment conjecture", which
limits the size of the minimal conflicts to revise. We demonstrate that this
conjecture brings us the interesting computational property of performing a
not-provable but global, revision, made of many local revisions, at a tractable
size. We illustrate this approach on an application.Comment: 14 page
A prototype-based resonance model of rhythm categorization
Categorization of rhythmic patterns is prevalent in musical practice, an example of this being the transcription of (possibly not strictly metrical) music into musical notation. In this article we implement a dynamical systems' model of rhythm categorization based on the resonance theory of rhythm perception developed by Large (2010). This model is used to simulate the categorical choices of participants in two experiments of Desain and Honing (2003). The model accurately replicates the experimental data. Our results support resonance theory as a viable model of rhythm perception and show that by viewing rhythm perception as a dynamical system it is possible to model central properties of rhythm categorization
Towards a Conceptualization of Sociomaterial Entanglement
In knowledge representation, socio-technical systems can be modeled
as multiagent systems in which the local knowledge of each individual agent can
be seen as a context. In this paper we propose formal ontologies as a means to
describe the assumptions driving the construction of contexts as local theories and
to enable interoperability among them. In particular, we present two alternative
conceptualizations of the notion of sociomateriality (and entanglement), which
is central in the recent debates on socio-technical systems in the social sciences,
namely critical and agential realism.
We thus start by providing a model of entanglement according to the critical realist
view, representing it as a property of objects that are essentially dependent on
different modules of an already given ontology. We refine then our treatment by
proposing a taxonomy of sociomaterial entanglements that distinguishes between
ontological and epistemological entanglement. In the final section, we discuss the
second perspective, which is more challenging form the point of view of knowledge
representation, and we show that the very distinction of information into
modules can be at least in principle built out of the assumption of an entangled
reality
Comparing theories: the dynamics of changing vocabulary. A case-study in relativity theory
There are several first-order logic (FOL) axiomatizations of special
relativity theory in the literature, all looking essentially different but
claiming to axiomatize the same physical theory. In this paper, we elaborate a
comparison, in the framework of mathematical logic, between these FOL theories
for special relativity. For this comparison, we use a version of mathematical
definability theory in which new entities can also be defined besides new
relations over already available entities. In particular, we build an
interpretation of the reference-frame oriented theory SpecRel into the
observationally oriented Signalling theory of James Ax. This interpretation
provides SpecRel with an operational/experimental semantics. Then we make
precise, "quantitative" comparisons between these two theories via using the
notion of definitional equivalence. This is an application of logic to the
philosophy of science and physics in the spirit of Johan van Benthem's work.Comment: 27 pages, 8 figures. To appear in Springer Book series Trends in
Logi
Semantic distillation: a method for clustering objects by their contextual specificity
Techniques for data-mining, latent semantic analysis, contextual search of
databases, etc. have long ago been developed by computer scientists working on
information retrieval (IR). Experimental scientists, from all disciplines,
having to analyse large collections of raw experimental data (astronomical,
physical, biological, etc.) have developed powerful methods for their
statistical analysis and for clustering, categorising, and classifying objects.
Finally, physicists have developed a theory of quantum measurement, unifying
the logical, algebraic, and probabilistic aspects of queries into a single
formalism. The purpose of this paper is twofold: first to show that when
formulated at an abstract level, problems from IR, from statistical data
analysis, and from physical measurement theories are very similar and hence can
profitably be cross-fertilised, and, secondly, to propose a novel method of
fuzzy hierarchical clustering, termed \textit{semantic distillation} --
strongly inspired from the theory of quantum measurement --, we developed to
analyse raw data coming from various types of experiments on DNA arrays. We
illustrate the method by analysing DNA arrays experiments and clustering the
genes of the array according to their specificity.Comment: Accepted for publication in Studies in Computational Intelligence,
Springer-Verla
Modelling concept prototype competencies using a developmental memory model
The use of concepts is fundamental to human-level cognition, but there remain a number of open questions as to the structures supporting this competence. Specifically, it has been shown that humans use concept prototypes, a flexible means of representing concepts such that it can be used both for categorisation and for similarity judgements. In the context of autonomous robotic agents, the processes by which such concept functionality could be acquired would be particularly useful, enabling flexible knowledge representation and application. This paper seeks to explore this issue of autonomous concept acquisition. By applying a set of structural and operational principles, that support a wide range of cognitive competencies, within a developmental framework, the intention is to explicitly embed the development of concepts into a wider framework of cognitive processing. Comparison with a benchmark concept modelling system shows that the proposed approach can account for a number of features, namely concept-based classification, and its extension to prototype-like functionality
Ontologies, Mental Disorders and Prototypes
As it emerged from philosophical analyses and cognitive research, most concepts exhibit typicality effects, and resist to the efforts of defining them in terms of necessary and sufficient conditions. This holds also in the case of many medical concepts. This is a problem for the design of computer science ontologies, since knowledge representation formalisms commonly adopted in this field do not allow for the representation of concepts in terms of typical traits. However, the need of representing concepts in terms of typical traits concerns almost every domain of real world knowledge, including medical domains. In particular, in this article we take into account the domain of mental disorders, starting from the DSM-5 descriptions of some specific mental disorders. On this respect, we favor a hybrid approach to the representation of psychiatric concepts, in which ontology oriented formalisms are combined to a geometric representation of knowledge based on conceptual spaces
Interoperable multimedia metadata through similarity-based semantic web service discovery
The increasing availability of multimedia (MM) resources, Web services as well as content, on the Web raises the need to automatically discover and process resources out of distributed repositories. However, the heterogeneity of applied metadata schemas and vocabularies â ranging from XML-based schemas such as MPEG-7 to formal knowledge representation approaches â raises interoperability problems. To enable MM metadata interoperability by means of automated similarity-computation, we propose a hybrid representation approach which combines symbolic MM metadata representations with a grounding in so-called Conceptual Spaces (CS). In that, we enable automatic computation of similarities across distinct metadata vocabularies and schemas in terms of spatial distances in shared CS. Moreover, such a vector-based approach is particularly well suited to represent MM metadata, given that a majority of MM parameters is provided in terms of quantified metrics. To prove the feasibility of our approach, we provide a prototypical implementation facilitating similarity-based discovery of publicly available MM services, aiming at federated MM content retrieval out of heterogeneous repositories
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