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Creation of ontology remains as a difficult task. Ontology bootstrapping is one of the technique, depends on a set of pre-defined textual sources like web services. The advantage of web services usual Abstract - Add to MetaCart Abstract: Ontologies have become the best modeling tool, in many applications majorly semantic web.
The advantage of web services usually consists of both WSDL and free text descriptors. The bootstrapping method using large repository of real-world web services has a drawback of revisiting of the concepts again and again. Our proposed method for ontology creation with an revisiting avoidance algorithm, this algorithm helps us to overcome from revisiting strategies in the bootstrapping ontologies.
The introduced algorithm will produce the efficient result as described this is paper. Huzita, Alberto B. Global Software Development GSD brought competitive advantages to organizations, but it has also imposed some drawbacks due to the physical distribution. A critical aspect of this approach is related to communication. In order to provide the same semantic understanding about information exchanged Abstract - Add to MetaCart Global Software Development GSD brought competitive advantages to organizations, but it has also imposed some drawbacks due to the physical distribution.
In order to provide the same semantic understanding about information exchanged on the environment to all team members it is necessary to minimize the ambiguity. This paper presents OntoDiSENv1, application ontology for a distributed software development environment.
The goal of this ontology is support communication among geographically dispersed team members. The ontology is integrated to a contextual information dissemination model, which notifies the team members about the actions that occur on the shared workspace and can influence their work.
The main contribution of OntoDiSENv1 is to support contextual information representation and processing, providing inference capability and semantic consistency of the information disseminated. Software Project Management is a knowledge intensive process that can benefit substantially from ontology development and ontology engineering. Ontology development could facilitate or improve substantially the software development process through the improvement of knowledge manage-ment, the increa Abstract - Add to MetaCart Software Project Management is a knowledge intensive process that can benefit substantially from ontology development and ontology engineering.
Ontology development could facilitate or improve substantially the software development process through the improvement of knowledge manage-ment, the increase of software and artefacts reusability, and the establishment of internal consis-tency within project management processes of various phases of software life cycle. A large number of ontologies have been developed attempting to address various software engineering aspects, such as requirements engineering, components reuse, domain modelling, etc.
In this paper, we present a systematic literature review focusing on software project management ontologies. The literature review, among other, has identified lack of standardization in terminology and concepts, lack of systematic domain modelling and use of ontologies mainly in prototype ontology systems that ad-dress rather limited aspects of software project management processes. This is understood to be a potential usability problem, and an area for further work.
A factor believed to be limiting the success of this method is the fact that resolving ODP concepts and properties to corresponding concepts and properties in natural language resources in this case WordNet is an error-prone process. This is largely due to the ambiguity of language and the fact that concepts in ODPs are generally described using only a single label per supported language. If pattern concepts were more thoroughly documented, using for instance more synonymous labels, class sense disambiguation would likely work better, and ODP search consequently work better also.
Additionally, WordNet does contain parts of questionable quality both in terms of coverage and structure , the improvement of which may lead to increased quality of results for dependent methods such as the one presented here. Most of these heuristics are very simple and make use of basic string matching techniques across labels or concept URIs e.
While end-users would be able to connect such concepts themselves by hand, suggesting them to the user will still save them considerable work, as they do not themselves have to dig through the subsumption hierarchy to locate the classes and properties. These heuristics are being coupled with a confidence scoring mechanism based on the scope of control of an ontology engineering project.
This scope defines which namespaces in the project that are allowed to be modified when performing ODP composition. Redefining the semantics of concepts outside of the scope of control is not recommended. Consequently, composition subsumption axioms in which concepts outside of the scope of control are defined as the subconcepts, are penalised and ranked lower than axioms which do not give rise to such a situation.
From the same study it was observed that all of the mapping axioms used to composite an ODP specialisation module into a resulting ontology were subsumption mappings i. Equivalence mappings were not used at all. This may indicate a cognitive understanding of the domain of discourse as being layered, that is to say, that ODP specialisation modules represent a layer of understanding which is more general than the final ontology, but mer specific than the original ODP.
If this observation holds also in a larger set of ontologies and ODPs, it may indicate that the border between ODP specialisation and ODP composition is not as clear cut as previously thought, and that tooling for specialisation and composition would need be more tightly integrated. This paper has introduced and discussed some concrete challenges regarding the use of Ontology Design Patterns, with an emphasis on tooling-related challenges that prevent non-expert users from performing Ontology Engineering using such patterns.
Those challenges primarily concern; a the task of finding patterns, b decisions to make when integrating pattern based modules with an existing ontology, and, c pattern and tooling quality.
The author has developed an ODP search method exploiting both the similarity between pattern competency questions and user queries, and the relative abstraction level of general pattern solutions versus concrete user queries, a method shown to increase recall when searching for candidate ODPs significantly.
Future work regarding ODP findability includes improving recall and precision further, and to examine which type of criteria users want to be able to filter results based on. The author has also developed a set of heuristics for ODP composition suggestions, and a confidence scoring method based on the scope of control of an ODP-based ontology engineering project, presently being implemented into a tool for guiding ODP composition. Future work regarding ODP composition includes tackling the more difficult alignments, possibly via enrichment using lexical resources.
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This idea has gained some traction within the academic community, as evidenced by the Workshop on Ontology Patterns series of workshops held on conjunction with the International Semantic Web Conference. However, the adoption of ODPs among practitioners is still quite limited. The eXtreme Design method provides recommendations on how one should structure an Ontology Engineering project of non-trivial size, from tasks and processes of larger granularity project initialisation, requirements elicitation, etc.
Those specific pattern usage tasks which are also applicable in other pattern-using development methods are: 1. Finding patterns relevant to the particular modelling issue. Adapting those general patterns to the modelling use case. Having located a pattern appropriate for reuse in a specific scenario, the ontology engineer needs to adapt and specialise said pattern for the scenario in question.
The specific steps vary from case to case, but a general approach that works in the majority of cases is as follows: 1. Specialise leaf classes of the subclass tree. Specialise leaf properties of the subproperty tree. Users performing such tasks are often confused by the many choices open to them, and the potential consequences of these choices, not limited to: Which mapping axioms should be used between the existing classes and properties and those of the solution module, e.
Each question was matched to one or more ODPs suitable for building an ontology supporting the question. This matching was performed by two senior ontology experts independently, and their respective answer sets merged.
The two experts reported very similar pattern selections in the cases where only a single pattern candidate existed in the pattern repository compliant with a competency question e. Recall was defined as the ratio of such expert-provided ODP candidates that the automated system retrieves for a given input question. Table 1.
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