4,965 research outputs found
Viewpoints on emergent semantics
Authors include:Philippe CudrÂŽe-Mauroux, and Karl Aberer (editors),
Alia I. Abdelmoty, Tiziana Catarci, Ernesto Damiani,
Arantxa Illaramendi, Robert Meersman,
Erich J. Neuhold, Christine Parent, Kai-Uwe Sattler,
Monica Scannapieco, Stefano Spaccapietra,
Peter Spyns, and Guy De TrÂŽeWe introduce a novel view on how to deal with the problems of semantic interoperability in distributed systems. This view is based on the concept of emergent semantics, which sees both the representation of semantics and the discovery of the proper interpretation of symbols as the result of a self-organizing process performed by distributed agents exchanging symbols and having utilities dependent on the proper interpretation of the symbols. This is a complex systems perspective on the problem of dealing with semantics. We highlight some of the distinctive features of our vision and point out preliminary examples of its applicatio
A fuzzy approach to similarity in Case-Based Reasoning suitable to SQL implementation
The aim of this paper is to formally introduce a notion of acceptance and similarity,
based on fuzzy logic, among case features in a case retrieval system. This is pursued
by rst reviewing the relationships between distance-based similarity (i.e. the
standard approach in CBR) and fuzzy-based similarity, with particular attention
to the formalization of a case retrieval process based on fuzzy query specication.
In particular, we present an approach where local acceptance relative to a feature
can be expressed through fuzzy distributions on its domain, abstracting the actual
values to linguistic terms. Furthermore, global acceptance is completely grounded
on fuzzy logic, by means of the usual combinations of local distributions through
specic dened norms. We propose a retrieval architecture, based on the above notions
and realized through a fuzzy extension of SQL, directly implemented on a
standard relational DBMS. The advantage of this approach is that the whole power
of an SQL engine can be fully exploited, with no need of implementing specic
retrieval algorithms. The approach is illustrated by means of some examples from
a recommender system called MyWine, aimed at recommending the suitable wine
bottles to a customer providing her requirements in both crisp and fuzzy way
Treatment of imprecision in data repositories with the aid of KNOLAP
Traditional data repositories introduced for the needs of business
processing, typically focus on the storage and querying of crisp
domains of data. As a result, current commercial data repositories
have no facilities for either storing or querying imprecise/
approximate data.
No significant attempt has been made for a generic and applicationindependent
representation of value imprecision mainly as a
property of axes of analysis and also as part of dynamic
environment, where potential users may wish to define their âownâ
axes of analysis for querying either precise or imprecise facts. In
such cases, measured values and facts are characterised by
descriptive values drawn from a number of dimensions, whereas
values of a dimension are organised as hierarchical levels.
A solution named H-IFS is presented that allows the representation
of flexible hierarchies as part of the dimension structures. An
extended multidimensional model named IF-Cube is put forward,
which allows the representation of imprecision in facts and
dimensions and answering of queries based on imprecise
hierarchical preferences. Based on the H-IFS and IF-Cube
concepts, a post relational OLAP environment is delivered, the
implementation of which is DBMS independent and its performance
solely dependent on the underlying DBMS engine
Aspects of dealing with imperfect data in temporal databases
In reality, some objects or concepts have properties with a time-variant or time-related nature. Modelling these kinds of objects or concepts in a (relational) database schema is possible, but time-variant and time-related attributes have an impact on the consistency of the entire database. Therefore, temporal database models have been proposed to deal with this. Time itself can be at the source of imprecision, vagueness and uncertainty, since existing time measuring devices are inherently imperfect. Accordingly, human beings manage time using temporal indications and temporal notions, which may contain imprecision, vagueness and uncertainty. However, the imperfection in human-used temporal indications is supported by human interpretation, whereas information systems need extraordinary support for this. Several proposals for dealing with such imperfections when modelling temporal aspects exist. Some of these proposals consider the basis of the system to be the conversion of the specificity of temporal notions between used temporal expressions. Other proposals consider the temporal indications in the used temporal expressions to be the source of imperfection. In this chapter, an overview is given, concerning the basic concepts and issues related to the modelling of time as such or in (relational) database models and the imperfections that may arise during or as a result of this modelling. Next to this, a novel and currently researched technique for handling some of these imperfections is presented
Music information retrieval: conceptuel framework, annotation and user behaviour
Understanding music is a process both based on and influenced by the knowledge and experience of the listener. Although content-based music retrieval has been given increasing attention in recent years, much of the research still focuses on bottom-up retrieval techniques. In order to make a music information retrieval system appealing and useful to the user, more effort should be spent on constructing systems that both operate directly on the encoding of the physical energy of music and are flexible with respect to usersâ experiences.
This thesis is based on a user-centred approach, taking into account the mutual relationship between music as an acoustic phenomenon and as an expressive phenomenon. The issues it addresses are: the lack of a conceptual framework, the shortage of annotated musical audio databases, the lack of understanding of the behaviour of system users and shortage of user-dependent knowledge with respect to high-level features of music.
In the theoretical part of this thesis, a conceptual framework for content-based music information retrieval is defined. The proposed conceptual framework - the first of its kind - is conceived as a coordinating structure between the automatic description of low-level music content, and the description of high-level content by the system users. A general framework for the manual annotation of musical audio is outlined as well. A new methodology for the manual annotation of musical audio is introduced and tested in case studies. The results from these studies show that manually annotated music files can be of great help in the development of accurate analysis tools for music information retrieval.
Empirical investigation is the foundation on which the aforementioned theoretical framework is built. Two elaborate studies involving different experimental issues are presented. In the first study, elements of signification related to spontaneous user behaviour are clarified. In the second study, a global profile of music information retrieval system users is given and their description of high-level content is discussed. This study has uncovered relationships between the usersâ demographical background and their perception of expressive and structural features of music. Such a multi-level approach is exceptional as it included a large sample of the population of real users of interactive music systems. Tests have shown that the findings of this study are representative of the targeted population.
Finally, the multi-purpose material provided by the theoretical background and the results from empirical investigations are put into practice in three music information retrieval applications: a prototype of a user interface based on a taxonomy, an annotated database of experimental findings and a prototype semantic user recommender system.
Results are presented and discussed for all methods used. They show that, if reliably generated, the use of knowledge on users can significantly improve the quality of music content analysis. This thesis demonstrates that an informed knowledge of human approaches to music information retrieval provides valuable insights, which may be of particular assistance in the development of user-friendly, content-based access to digital music collections
A Computational-Hermeneutic Approach for Conceptual Explicitation
We present a computer-supported approach for the logical analysis and
conceptual explicitation of argumentative discourse. Computational hermeneutics
harnesses recent progresses in automated reasoning for higher-order logics and
aims at formalizing natural-language argumentative discourse using flexible
combinations of expressive non-classical logics. In doing so, it allows us to
render explicit the tacit conceptualizations implicit in argumentative
discursive practices. Our approach operates on networks of structured arguments
and is iterative and two-layered. At one layer we search for logically correct
formalizations for each of the individual arguments. At the next layer we
select among those correct formalizations the ones which honor the argument's
dialectic role, i.e. attacking or supporting other arguments as intended. We
operate at these two layers in parallel and continuously rate sentences'
formalizations by using, primarily, inferential adequacy criteria. An
interpretive, logical theory will thus gradually evolve. This theory is
composed of meaning postulates serving as explications for concepts playing a
role in the analyzed arguments. Such a recursive, iterative approach to
interpretation does justice to the inherent circularity of understanding: the
whole is understood compositionally on the basis of its parts, while each part
is understood only in the context of the whole (hermeneutic circle). We
summarily discuss previous work on exemplary applications of human-in-the-loop
computational hermeneutics in metaphysical discourse. We also discuss some of
the main challenges involved in fully-automating our approach. By sketching
some design ideas and reviewing relevant technologies, we argue for the
technological feasibility of a highly-automated computational hermeneutics.Comment: 29 pages, 9 figures, to appear in A. Nepomuceno, L. Magnani, F.
Salguero, C. Bar\'es, M. Fontaine (eds.), Model-Based Reasoning in Science
and Technology. Inferential Models for Logic, Language, Cognition and
Computation, Series "Sapere", Springe
INTELLIGENT TECHNIQUES FOR HANDLING UNCERTAINTY IN THE ASSESSMENT OF NEONATAL OUTCOME
Objective assessment of the neonatal outcome of labour is important, but it is a difficult
and challenging problem. It is an invaluable source of information which can be used to
provide feedback to clinicians, to audit a unit's overall performance, and can guide subsequent
neonatal care. Current methods are inadequate as they fail to distinguish damage that
occurred during labour from damage that occurred before or after labour. Analysis of the
chemical acid-base status of blood taken from the umbilical cord of an infant immediately
after delivery provides information on any damage suffered by the infant due to lack of oxygen
during labour. However, this process is complex and error prone, and requires expertise
which is not always available on labour wards.
A model of clinical expertise required for the accurate interpretation of umbilical acid-base
status was developed, and encapsulated in a rule-based expert system. This expert system
checks results to ensure their consistency, identifies whether the results come from arterial
or venous vessels, and then produces an interpretation of their meaning. This 'crisp' expert
system was validated, verified and commercially released, and has since been installed at
twenty two hospitals all around the United Kingdom.
The assessment of umbilical acid-base status is characterised by uncertainty in both the basic
data and the knowledge required for its interpretation. Fuzzy logic provides a technique
for representing both these forms of uncertainty in a single framework. A 'preliminary'
fuzzy-logic based expert system to interpret error-free results was developed, based on the
knowledge embedded in the crisp expert system. Its performance was compared against clinicians
in a validation test, but initially its performance was found to be poor in comparison
with the clinicians and inferior to the crisp expert system. An automatic tuning algorithm
was developed to modify the behaviour of the fuzzy model utilised in the expert system.
Sub-normal membership functions were used to weight terms in the fuzzy expert system in
a novel manner. This resulted in an improvement in the performance of the fuzzy expert
system to a level comparable to the clinicians, and superior to the crisp expert system.
Experimental work was carried out to evaluate the imprecision in umbilical cord acid-base
parameters. This information, in conjunction with fresh knowledge elicitation sessions, allowed
the creation of a more comprehensive fuzzy expert system, to validate and interpret
all acid-base data. This 'integrated' fuzzy expert system was tuned using the comparison
data obtained previously, and incorporated vessel identification rules and interpretation rules,
with numeric and linguistic outputs for each. The performance of each of the outputs was
evaluated in a rigorous validation study. This demonstrated excellent agreement with the
experts for the numeric outputs, and agreement on a par with the experts for the linguistic
outputs. The numeric interpretation produced by the fuzzy expert system is a novel single
dimensional measure that accurately represents the severity of acid-base results.
The development of the crisp and fuzzy expert systems represents a major achievement and
constitutes a significant contribution to the assessment of neonatal outcome.Plymouth Postgraduate Medical Schoo
An Introduction to Ontology
Analytical philosophy of the last one hundred years has been heavily influenced by a doctrine to the effect that one can arrive at a correct ontology by paying attention to certain superficial (syntactic) features of first-order predicate logic as conceived by Frege and Russell. More specifically, it is a doctrine to the effect that the key to the ontological structure of reality is captured syntactically in the âFaâ (or, in more sophisticated versions, in the âRabâ) of first-order logic, where âFâ stands for what is general in reality and âaâ for what is individual. Hence âf(a)ntologyâ. Because predicate logic has exactly two syntactically different kinds of referring expressionsââFâ, âGâ, âRâ, etc., and âaâ, âbâ, âcâ, etc.âso reality must consist of exactly two correspondingly different kinds of entity: the general (properties, concepts) and the particular (things, objects), the relation between these two kinds of entity being revealed in the predicate-argument structure of atomic formulas in first-order logic
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