Techniques for automated taxonomy building: towards ontologies for knowledge management

Ontologies have become widely accepted as the main method for representing knowledge in Knowledge Management (KM) applica-tions. Given the continuous and rapid change and dynamic nature of knowledge in all fields, automated methods for construct-ing ontologies are of great importance. All ontologies or taxonomies currently in use have been hand built and require consider-able manpower to keep up to date. Taxono-mies are less logically rigorous than ontolo-gies, and in this paper we consider the re-quirements for a system which automatically constructed taxonomies. There are a number of potentially useful methods for construct-ing hierarchically organised concepts from a collection of texts and there are a number of automatic methods which permit one to as-sociate one word with another. The impor-tant issue for the successful development of this research area is to identify techniques for labelling the relation between two candi-date terms, if one exists. We consider a number of possible approaches and argue that the majority are unsuitable for our re-quirements.

An investigation into children’s inductive reasoning strategies:What drives the development of category induction?

In a series of studies, I investigated the developmental changes in children’s inductive reasoning strategy, methodological manipulations affecting the trajectory, and driving mechanisms behind the development of category induction. I systematically controlled the nature of the stimuli used, and employed a triad paradigm in which perceptual cues were directly pitted against category membership, to explore under which circumstances children used perceptual or category induction. My induction tasks were designed for children aged 3-9 years old using biologically plausible novel items. In Study 1, I tested 264 children. Using a wide age range allowed me to systematically investigate the developmental trajectory of induction. I also created two degrees of perceptual distractor – high and low – and explored whether the degree of perceptual similarity between target and test items altered children’s strategy preference. A further 52 children were tested in Study 2, to examine whether children showing a perceptual-bias were in fact basing their choice on maturation categories. A gradual transition was observed from perceptual to category induction. However, this transition could not be due to the inability to inhibit high perceptual distractors as children of all ages were equally distracted. Children were also not basing their strategy choices on maturation categories. In Study 3, I investigated category structure (featural vs. relational category rules) and domain (natural vs. artefact) on inductive preference. I tested 403 children. Each child was assigned to either the featural or relational condition, and completed both a natural kind and an artefact task. A further 98 children were tested in Study 4, on the effect of using stimuli labels during the tasks. I observed the same gradual transition from perceptual to category induction preference in Studies 3 and 4. This pattern was stable across domains, but children developed a category-bias one year later for relational categories, arguably due to the greater demands on executive function (EF) posed by these stimuli. Children who received labels during the task made significantly more category choices than those who did not receive labels, possibly due to priming effects. Having investigated influences affecting the developmental trajectory, I continued by exploring the driving mechanism behind the development of category induction. In Study 5, I tested 60 children on a battery of EF tasks as well as my induction task. None of the EF tasks were able to predict inductive variance, therefore EF development is unlikely to be the driving factor behind the transition. Finally in Study 6, I divided 252 children into either a comparison group or an intervention group. The intervention group took part in an interactive educational session at Twycross Zoo about animal adaptations. Both groups took part in four induction tasks, two before and two a week after the zoo visits. There was a significant increase in the number of category choices made in the intervention condition after the zoo visit, a result not observed in the comparison condition. This highlights the role of knowledge in supporting the transition from perceptual to category induction. I suggest that EF development may support induction development, but the driving mechanism behind the transition is an accumulation of knowledge, and an appreciation for the importance of category membership.

The growing importance of inter-company collaboration

Guest editorial: This special issue has been drawn from papers that were published as part of the Second European Conference on Management of Technology (EuroMOT) which was held at Aston Business School (Birmingham, UK) 10-12 September 2006. This was the official European conference for the International Association for Management of Technology (IAMOT); the overall theme of the conference was “Technology and global integration.” There were many high-calibre papers submitted to the conference and published in the associated proceedings (Bennett et al., 2006). The streams of interest that emerged from these submissions were the importance of: technology strategy, innovation, process technologies, managing change, national policies and systems, research and development, supply chain technology, service and operational technology, education and training, small company incubation, technology transfer, virtual operations, technology in developing countries, partnership and alliance, and financing and investment. This special issue focuses upon the streams of interest that accentuate the importance of collaboration between different organisations. Such organisations vary greatly in character; for instance, they may be large or small, publicly or privately owned, and operate in manufacturing or service sectors. Despite these varying characteristics they all have something in common; they all stress the importance of inter-organisational collaboration as a critical success factor for their organisation. In today's global economy it is essential that organisations decide what their core competencies are what those of complementing organisations are. Core competences should be developed to become a bases of differentiation, leverage and competitive advantage, whilst those that are less mature should be outsourced to other organisations that can claim to have had more recognition and success in that particular core competence (Porter, 2001). This strategic trend can be observed throughout advanced economies and is growing strongly. If a posteriori reasoning is applied here it follows that organisations could continue to become more specialised in fewer areas whilst simultaneously becoming more dependent upon other organisations for critical parts of their operations. Such actions seem to fly in the face of rational business strategy and so the question must be asked: why are organisations developing this way? The answer could lie in the recent changes in endogenous and exogenous factors of the organisation; the former emphasising resource-based issues in the short-term, and strategic positioning in the long-term whilst the later emphasises transaction costs in the short-term and acquisition of new skills and knowledge in the long-term. For a harmonious balance of these forces to prevail requires organisations to firstly declare a shared meta-strategy, then to put some cross-organisational processes into place which have their routine operations automated as far as possible. A rolling business plan would review, assess and reposition each organisation within this meta-strategy according to how well they have contributed (Binder and Clegg, 2006). The important common issue here is that an increasing number of businesses today are gaining direct benefit from increasing their levels of inter-organisational collaboration. Such collaboration has largely been possible due to recent technological advances which can make organisational structures more agile (e.g. the extended or the virtual enterprise), organisational infra-structure more connected, and the sharing of real-time information an operational reality. This special issue consists of research papers that have explored the above phenomenon in some way. For instance, the role of government intervention, the use of internet-based technologies, the role of research and development organisations, the changing relationships between start-ups and established firms, the importance of cross-company communities of practice, the practice of networking, the front-loading of large-scale projects, innovation and the probabilistic uncertainties that organisations experience are explored in these papers. The cases cited in these papers are limited as they have a Eurocentric focus. However, it is hoped that readers of this special issue will gain a valuable insight into the increasing importance of collaborative practices via these studies.

Retrieving designs from a sketch using an automated GT coding and classification system

While the retrieval of existing designs to prevent unnecessary duplication of parts is a recognised strategy in the control of design costs the available techniques to achieve this, even in product data management systems, are limited in performance or require large resources. A novel system has been developed based on a new version of an existing coding system (CAMAC) that allows automatic coding of engineering drawings and their subsequent retrieval using a drawing of the desired component as the input. The ability to find designs using a detail drawing rather than textual descriptions is a significant achievement in itself. Previous testing of the system has demonstrated this capability but if a means could be found to find parts from a simple sketch then its practical application would be much more effective. This paper describes the development and testing of such a search capability using a database of over 3000 engineering components.

Stimulating design reuse through automated coding

In designing new product the ability to retrieve drawings of existing components is important if costs are to be controlled by preventing unnecessary duplication if parts. Component coding and classification systems have been used successfully for these purposes but suffer from high operational costs and poor usability arising directly from the manual nature of the coding process itself. A new version of an existing coding system (CAMAC) has been developed to reduce costs by automatically coding engineering drawings. Usability is improved be supporting searches based on a drawing or sketch of the desired component. Test results from a database of several thousand drawings are presented.

Lexical database enrichment through semi-automated morphological analysis

Derivational morphology proposes meaningful connections between words and is largely unrepresented in lexical databases. This thesis presents a project to enrich a lexical database with morphological links and to evaluate their contribution to disambiguation. A lexical database with sense distinctions was required. WordNet was chosen because of its free availability and widespread use. Its suitability was assessed through critical evaluation with respect to specifications and criticisms, using a transparent, extensible model. The identification of serious shortcomings suggested a portable enrichment methodology, applicable to alternative resources. Although 40% of the most frequent words are prepositions, they have been largely ignored by computational linguists, so addition of prepositions was also required. The preferred approach to morphological enrichment was to infer relations from phenomena discovered algorithmically. Both existing databases and existing algorithms can capture regular morphological relations, but cannot capture exceptions correctly; neither of them provide any semantic information. Some morphological analysis algorithms are subject to the fallacy that morphological analysis can be performed simply by segmentation. Morphological rules, grounded in observation and etymology, govern associations between and attachment of suffixes and contribute to defining the meaning of morphological relationships. Specifying character substitutions circumvents the segmentation fallacy. Morphological rules are prone to undergeneration, minimised through a variable lexical validity requirement, and overgeneration, minimised by rule reformulation and restricting monosyllabic output. Rules take into account the morphology of ancestor languages through co-occurrences of morphological patterns. Multiple rules applicable to an input suffix need their precedence established. The resistance of prefixations to segmentation has been addressed by identifying linking vowel exceptions and irregular prefixes. The automatic affix discovery algorithm applies heuristics to identify meaningful affixes and is combined with morphological rules into a hybrid model, fed only with empirical data, collected without supervision. Further algorithms apply the rules optimally to automatically pre-identified suffixes and break words into their component morphemes. To handle exceptions, stoplists were created in response to initial errors and fed back into the model through iterative development, leading to 100% precision, contestable only on lexicographic criteria. Stoplist length is minimised by special treatment of monosyllables and reformulation of rules. 96% of words and phrases are analysed. 218,802 directed derivational links have been encoded in the lexicon rather than the wordnet component of the model because the lexicon provides the optimal clustering of word senses. Both links and analyser are portable to an alternative lexicon. The evaluation uses the extended gloss overlaps disambiguation algorithm. The enriched model outperformed WordNet in terms of recall without loss of precision. Failure of all experiments to outperform disambiguation by frequency reflects on WordNet sense distinctions.

Transformational leadership and moral reasoning

Terms such as moral and ethical leadership are used widely in theory, yet little systematic research has related a sociomoral dimension to leadership in organizations. This study investigated whether managers' moral reasoning (n=132) was associated with the transformational and transactional leadership behaviors they exhibited as perceived by their subordinates (n=407). Managers completed the Defining Issues Test (J. R. Rest, 1990), whereas their subordinates completed the Multifactor Leadership Questionnaire (B. M. Bass & B. J. Avolio, 1995). Analysis of covariance indicated that managers scoring in the highest group of the moral-reasoning distribution exhibited more transformational leadership behaviors than leaders scoring in the lowest group. As expected, there was no relationship between moral-reasoning group and transactional leadership behaviors. Implications for leadership development are discussed.

Present perspectives on the automated classification of the G-protein coupled receptors (GPCRs) at the protein sequence level

The G-protein coupled receptors--or GPCRs--comprise simultaneously one of the largest and one of the most multi-functional protein families known to modern-day molecular bioscience. From a drug discovery and pharmaceutical industry perspective, the GPCRs constitute one of the most commercially and economically important groups of proteins known. The GPCRs undertake numerous vital metabolic functions and interact with a hugely diverse range of small and large ligands. Many different methodologies have been developed to efficiently and accurately classify the GPCRs. These range from motif-based techniques to machine learning as well as a variety of alignment-free techniques based on the physiochemical properties of sequences. We review here the available methodologies for the classification of GPCRs. Part of this work focuses on how we have tried to build the intrinsically hierarchical nature of sequence relations, implicit within the family, into an adaptive approach to classification. Importantly, we also allude to some of the key innate problems in developing an effective approach to classifying the GPCRs: the lack of sequence similarity between the six classes that comprise the GPCR family and the low sequence similarity to other family members evinced by many newly revealed members of the family.

INTAMAP: an interoperable automated interpolation web service

INTAMAP is a web processing service for the automatic interpolation of measured point data. Requirements were (i) using open standards for spatial data such as developed in the context of the open geospatial consortium (OGC), (ii) using a suitable environment for statistical modelling and computation, and (iii) producing an open source solution. The system couples the 52-North web processing service, accepting data in the form of an observations and measurements (O&M) document with a computing back-end realized in the R statistical environment. The probability distribution of interpolation errors is encoded with UncertML, a new markup language to encode uncertain data. Automatic interpolation needs to be useful for a wide range of applications and the algorithms have been designed to cope with anisotropies and extreme values. In the light of the INTAMAP experience, we discuss the lessons learnt.

Automated mapping of environmental variables from a SEIS or SISE perspective

The INTAMAP FP6 project has developed an interoperable framework for real-time automatic mapping of critical environmental variables by extending spatial statistical methods and employing open, web-based, data exchange protocols and visualisation tools. This paper will give an overview of the underlying problem, of the project, and discuss which problems it has solved and which open problems seem to be most relevant to deal with next. The interpolation problem that INTAMAP solves is the generic problem of spatial interpolation of environmental variables without user interaction, based on measurements of e.g. PM10, rainfall or gamma dose rate, at arbitrary locations or over a regular grid covering the area of interest. It deals with problems of varying spatial resolution of measurements, the interpolation of averages over larger areas, and with providing information on the interpolation error to the end-user. In addition, monitoring network optimisation is addressed in a non-automatic context.