Ranking ontologies with AKTiveRank

Ontology search and reuse is becoming increasingly important as the quest for methods to reduce the cost of constructing such knowledge structures continues. A number of ontology libraries and search engines are coming to existence to facilitate locating and retrieving potentially relevant ontologies. The number of ontologies available for reuse is steadily growing, and so is the need for methods to evaluate and rank existing ontologies in terms of their relevance to the needs of the knowledge engineer. This paper presents AKTiveRank, a prototype system for ranking ontologies based on a number of structural metrics.

Metrics for ranking ontologies

Representing knowledge using domain ontologies has shown to be a useful mechanism and format for managing and exchanging information. Due to the difficulty and cost of building ontologies, a number of ontology libraries and search engines are coming to existence to facilitate reusing such knowledge structures. The need for ontology ranking techniques is becoming crucial as the number of ontologies available for reuse is continuing to grow. In this paper we present AKTiveRank, a prototype system for ranking ontologies based on the analysis of their structures. We describe the metrics used in the ranking system and present an experiment on ranking ontologies returned by a popular search engine for an example query.

AKTive Food:semantic web based knowledge conduits for the organic food industry

We present a vision and a proposal for using Semantic Web technologies in the organic food industry. This is a very knowledge intensive industry at every step from the producer, to the caterer or restauranteur, through to the consumer. There is a crucial need for a concept of environmental audit which would allow the various stake holders to know the full environmental impact of their economic choices. This is a di?erent and parallel form of knowledge to that of price. Semantic Web technologies can be used e?ectively for the calculation and transfer of this type of knowledge (together with other forms of multimedia data) which could contribute considerably to the commercial and educational impact of the organic food industry. We outline how this could be achieved as our essential ob jective is to show how advanced technologies could be used to both reduce ecological impact and increase public awareness.

Natural language processing as a foundation of the semantic Web

The main argument of this paper is that Natural Language Processing (NLP) does, and will continue to, underlie the Semantic Web (SW), including its initial construction from unstructured sources like the World Wide Web (WWW), whether its advocates realise this or not. Chiefly, we argue, such NLP activity is the only way up to a defensible notion of meaning at conceptual levels (in the original SW diagram) based on lower level empirical computations over usage. Our aim is definitely not to claim logic-bad, NLP-good in any simple-minded way, but to argue that the SW will be a fascinating interaction of these two methodologies, again like the WWW (which has been basically a field for statistical NLP research) but with deeper content. Only NLP technologies (and chiefly information extraction) will be able to provide the requisite RDF knowledge stores for the SW from existing unstructured text databases in the WWW, and in the vast quantities needed. There is no alternative at this point, since a wholly or mostly hand-crafted SW is also unthinkable, as is a SW built from scratch and without reference to the WWW. We also assume that, whatever the limitations on current SW representational power we have drawn attention to here, the SW will continue to grow in a distributed manner so as to serve the needs of scientists, even if it is not perfect. The WWW has already shown how an imperfect artefact can become indispensable.

Comparison of near visual acuity and reading metrics in presbyopia correction

PURPOSE: To provide a consistent standard for the evaluation of different types of presbyopic correction. SETTING: Eye Clinic, School of Life and Health Sciences, Aston University, Birmingham, United Kingdom. METHODS: Presbyopic corrections examined were accommodating intraocular lenses (IOLs), simultaneous multifocal and monovision contact lenses, and varifocal spectacles. Binocular near visual acuity measured with different optotypes (uppercase letters, lowercase letters, and words) and reading metrics assessed with the Minnesota Near Reading chart (reading acuity, critical print size [CPS], CPS reading speed) were intercorrelated (Pearson product moment correlations) and assessed for concordance (intraclass correlation coefficients [ICC]) and agreement (Bland-Altman analysis) for indication of clinical usefulness. RESULTS: Nineteen accommodating IOL cases, 40 simultaneous contact lens cases, and 38 varifocal spectacle cases were evaluated. Other than CPS reading speed, all near visual acuity and reading metrics correlated well with each other (r>0.70, P<.001). Near visual acuity measured with uppercase letters was highly concordant (ICC, 0.78) and in close agreement with lowercase letters (+/- 0.17 logMAR). Near word acuity agreed well with reading acuity (+/- 0.16 logMAR), which in turn agreed well with near visual acuity measured with uppercase letters 0.16 logMAR). Concordance (ICC, 0.18 to 0.46) and agreement (+/- 0.24 to 0.30 logMAR) of CPS with the other near metrics was moderate. CONCLUSION: Measurement of near visual ability in presbyopia should be standardized to include assessment of near visual acuity with logMAR uppercase-letter optotypes, smallest logMAR print size that maintains maximum reading speed (CPS), and reading speed. J Cataract Refract Surg 2009; 35:1401-1409 (C) 2009 ASCRS and ESCRS

Does normal processing provide evidence of specialised semantic subsystems?

Category-specific disorders are frequently explained by suggesting that living and non-living things are processed in separate subsystems (e.g. Caramazza & Shelton, 1998). If subsystems exist, there should be benefits for normal processing, beyond the influence of structural similarity. However, no previous study has separated the relative influences of similarity and semantic category. We created novel examples of living and non-living things so category and similarity could be manipulated independently. Pre-tests ensured that our images evoked appropriate semantic information and were matched for familiarity. Participants were trained to associate names with the images and then performed a name-verification task under two levels of time pressure. We found no significant advantage for living things alongside strong effects of similarity. Our results suggest that similarity rather than category is the key determinant of speed and accuracy in normal semantic processing. We discuss the implications of this finding for neuropsychological studies. © 2005 Psychology Press Ltd.

An analysis of the semantic field of the German particles 'Uberhaupt' and 'Eigentlich'

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY WITH PRIOR ARRANGEMENT

A linguistic and semantic approach to the theory and practice of literary translation

This work explores the relevance of semantic and linguistic description to translation, theory and practice. It is aimed towards a practical model of approach to texts to translate. As literary texts [poetry mainly] are the focus of attention, so are stylistic matters. Note, however, that 'style', and, to some extent, the conclusions of the work, are not limited to so-called literary texts. The study of semantic description reveals that most translation problems do not stem from the cognitive (langue-related), but rather from the contextual (parole-related) aspects of meaning. Thus, any linguistic model that fails to account for the latter is bound to fall short. T.G.G. does, whereas Systemics, concerned with both the 'Iangue' and 'parole' (stylistic and sociolinguistic mainly) aspects of meaning, provides a useful framework of approach to texts to translate. Two essential semantic principles for translation are: that meaning is the property of a language (Firth); and the 'relativity of meaning assignments' (Tymoczko). Both imply that meaning can only be assessed, correctly, in the relevant socio-cultural background. Translation is seen as a restricted creation, and the translator's encroach as a three-dimensional critical one. To encompass the most technical to the most literary text, and account for variations in emphasis in any text, translation theory must be based on typology of function Halliday's ideational, interpersonal and textual, or, Buhler's symbol, signal, symptom, Functions3. Function Coverall and specific] will dictate aims and method, and also provide the critic with criteria to assess translation Faithfulness. Translation can never be reduced to purely objective methods, however. Intuitive procedures intervene, in textual interpretation and analysis, in the choice of equivalents, and in the reception of a translation. Ultimately, translation, theory and practice, may perhaps constitute the touchstone as regards the validity of linguistic and semantic theories.

A systematic exploration of perceptual and semantic differences in category-specific object-processing using magnetoencephalography

In a series of experiments, we tested category-specific activation in normal parti¬cipants using magnetoencephalography (MEG). Our experiments explored the temporal processing of objects, as MEG characterises neural activity on the order of milliseconds. Our experiments explored object-processing, including assessing the time-course of ob¬ject naming, early differences in processing living compared with nonliving objects and processing objects at the basic compared with the domain level, and late differences in processing living compared with nonliving objects and processing objects at the basic compared with the domain level. In addition to studies using normal participants, we also utilised MEG to explore category-specific processing in a patient with a deficit for living objects. Our findings support the cascade model of object naming (Humphreys et al., 1988). In addition, our findings using normal participants demonstrate early, category-specific perceptual differences. These findings are corroborated by our patient study. In our assessment of the time-course of category-specific effects as well as a separate analysis designed to measure semantic differences between living and nonliving objects, we found support for the sensory/motor model of object naming (Martin, 1998), in addition to support for the cascade model of object naming. Thus, object processing in normal participants appears to be served by a distributed network in the brain, and there are both perceptual and semantic differences between living and nonliving objects. A separate study assessing the influence of the level at which you are asked to identify an object on processing in the brain found evidence supporting the convergence zone hypothesis (Damasio, 1989). Taken together, these findings indicate the utility of MEG in exploring the time-course of object processing, isolating early perceptual and later semantic effects within the brain.

A semantic modelling approach to knowledge based statistical software

The topic of this thesis is the development of knowledge based statistical software. The shortcomings of conventional statistical packages are discussed to illustrate the need to develop software which is able to exhibit a greater degree of statistical expertise, thereby reducing the misuse of statistical methods by those not well versed in the art of statistical analysis. Some of the issues involved in the development of knowledge based software are presented and a review is given of some of the systems that have been developed so far. The majority of these have moved away from conventional architectures by adopting what can be termed an expert systems approach. The thesis then proposes an approach which is based upon the concept of semantic modelling. By representing some of the semantic meaning of data, it is conceived that a system could examine a request to apply a statistical technique and check if the use of the chosen technique was semantically sound, i.e. will the results obtained be meaningful. Current systems, in contrast, can only perform what can be considered as syntactic checks. The prototype system that has been implemented to explore the feasibility of such an approach is presented, the system has been designed as an enhanced variant of a conventional style statistical package. This involved developing a semantic data model to represent some of the statistically relevant knowledge about data and identifying sets of requirements that should be met for the application of the statistical techniques to be valid. Those areas of statistics covered in the prototype are measures of association and tests of location.

Semantic and organization considerations in database conceptual modelling : the Semantic Conceptual Organizational Model (SECOM)

This thesis presents a new approach to designing large organizational databases. The approach emphasizes the need for a holistic approach to the design process. The development of the proposed approach was based on a comprehensive examination of the issues of relevance to the design and utilization of databases. Such issues include conceptual modelling, organization theory, and semantic theory. The conceptual modelling approach presented in this thesis is developed over three design stages, or model perspectives. In the semantic perspective, concept definitions were developed based on established semantic principles. Such definitions rely on meaning - provided by intension and extension - to determine intrinsic conceptual definitions. A tool, called meaning-based classification (MBC), is devised to classify concepts based on meaning. Concept classes are then integrated using concept definitions and a set of semantic relations which rely on concept content and form. In the application perspective, relationships are semantically defined according to the application environment. Relationship definitions include explicit relationship properties and constraints. The organization perspective introduces a new set of relations specifically developed to maintain conformity of conceptual abstractions with the nature of information abstractions implied by user requirements throughout the organization. Such relations are based on the stratification of work hierarchies, defined elsewhere in the thesis. Finally, an example of an application of the proposed approach is presented to illustrate the applicability and practicality of the modelling approach.

Spatially structured cognitve models of semantic information:the implications for computerised databases

Existing theories of semantic cognition propose models of cognitive processing occurring in a conceptual space, where ‘meaning’ is derived from the spatial relationships between concepts’ mapped locations within the space. Information visualisation is a growing area of research within the field of information retrieval, and methods for presenting database contents visually in the form of spatial data management systems (SDMSs) are being developed. This thesis combined these two areas of research to investigate the benefits associated with employing spatial-semantic mapping (documents represented as objects in two- and three-dimensional virtual environments are proximally mapped dependent on the semantic similarity of their content) as a tool for improving retrieval performance and navigational efficiency when browsing for information within such systems. Positive effects associated with the quality of document mapping were observed; improved retrieval performance and browsing behaviour were witnessed when mapping was optimal. It was also shown using a third dimension for virtual environment (VE) presentation provides sufficient additional information regarding the semantic structure of the environment that performance is increased in comparison to using two-dimensions for mapping. A model that describes the relationship between retrieval performance and browsing behaviour was proposed on the basis of findings. Individual differences were not found to have any observable influence on retrieval performance or browsing behaviour when mapping quality was good. The findings from this work have implications for both cognitive modelling of semantic information, and for designing and testing information visualisation systems. These implications are discussed in the conclusions of this work.

Metrics and models to support the development of hybrid information systems

The research described here concerns the development of metrics and models to support the development of hybrid (conventional/knowledge based) integrated systems. The thesis argues from the point that, although it is well known that estimating the cost, duration and quality of information systems is a difficult task, it is far from clear what sorts of tools and techniques would adequately support a project manager in the estimation of these properties. A literature review shows that metrics (measurements) and estimating tools have been developed for conventional systems since the 1960s while there has been very little research on metrics for knowledge based systems (KBSs). Furthermore, although there are a number of theoretical problems with many of the `classic' metrics developed for conventional systems, it also appears that the tools which such metrics can be used to develop are not widely used by project managers. A survey was carried out of large UK companies which confirmed this continuing state of affairs. Before any useful tools could be developed, therefore, it was important to find out why project managers were not using these tools already. By characterising those companies that use software cost estimating (SCE) tools against those which could but do not, it was possible to recognise the involvement of the client/customer in the process of estimation. Pursuing this point, a model of the early estimating and planning stages (the EEPS model) was developed to test exactly where estimating takes place. The EEPS model suggests that estimating could take place either before a fully-developed plan has been produced, or while this plan is being produced. If it were the former, then SCE tools would be particularly useful since there is very little other data available from which to produce an estimate. A second survey, however, indicated that project managers see estimating as being essentially the latter at which point project management tools are available to support the process. It would seem, therefore, that SCE tools are not being used because project management tools are being used instead. The issue here is not with the method of developing an estimating model or tool, but; in the way in which "an estimate" is intimately tied to an understanding of what tasks are being planned. Current SCE tools are perceived by project managers as targetting the wrong point of estimation, A model (called TABATHA) is then presented which describes how an estimating tool based on an analysis of tasks would thus fit into the planning stage. The issue of whether metrics can be usefully developed for hybrid systems (which also contain KBS components) is tested by extending a number of "classic" program size and structure metrics to a KBS language, Prolog. Measurements of lines of code, Halstead's operators/operands, McCabe's cyclomatic complexity, Henry & Kafura's data flow fan-in/out and post-release reported errors were taken for a set of 80 commercially-developed LPA Prolog programs: By re~defining the metric counts for Prolog it was found that estimates of program size and error-proneness comparable to the best conventional studies are possible. This suggests that metrics can be usefully applied to KBS languages, such as Prolog and thus, the development of metncs and models to support the development of hybrid information systems is both feasible and useful.