44,087 research outputs found
Business Ontology for Evaluating Corporate Social Responsibility
This paper presents a software solution that is developed to automatically classify companies by taking into account their level of social responsibility. The application is based on ontologies and on intelligent agents. In order to obtain the data needed to evaluate companies, we developed a web crawling module that analyzes the companyâs website and the documents that are available online such as social responsibility report, mission statement, employment structure, etc. Based on a predefined CSR ontology, the web crawling module extracts the terms that are linked to corporate social responsibility. By taking into account the extracted qualitative data, an intelligent agent, previously trained on a set of companies, computes the qualitative values, which are then included in the classification model based on neural networks. The proposed ontology takes into consideration the guidelines proposed by the âISO 26000 Standard for Social Responsibilityâ. Having this model, and being aware of the positive relationship between Corporate Social Responsibility and financial performance, an overall perspective on each companyâs activity can be configured, this being useful not only to the companyâs creditors, auditors, stockholders, but also to its consumers.corporate social responsibility, ISO 26000 Standard for Social Responsibility, ontology, web crawling, intelligent agent, corporate performance, POS tagging, opinion mining, sentiment analysis
Using ontology engineering for understanding needs and allocating resources in web-based industrial virtual collaboration systems
In many interactions in cross-industrial and inter-industrial collaboration, analysis and understanding of relative specialist and non-specialist language is one of the most pressing challenges when trying to build multi-party, multi-disciplinary collaboration system. Hence, identifying the scope of the language used and then understanding the relationships between the language entities are key problems. In computer science, ontologies are used to provide a common vocabulary for a domain of interest together with descriptions of the meaning of terms and relationships between them, like in an encyclopedia. These, however, often lack the fuzziness required for human orientated systems. This paper uses an engineering sector business collaboration system (www.wmccm.co.uk) as a case study to illustrate the issues. The purpose of this paper is to introduce a novel ontology engineering methodology, which generates structurally enriched cross domain ontologies economically, quickly and reliably. A semantic relationship analysis of the Google Search Engine Index was devised and evaluated. Using Semantic analysis seems to generate a viable list of subject terms. A social network analysis of the semantically derived terms was conducted to generate a decision support network with rich relationships between terms. The derived ontology was quicker to generate, provided richer internal relationships and relied far less on expert contribution. More importantly, it improved the collaboration matching capability of WMCCM
Technology Integration around the Geographic Information: A State of the Art
One of the elements that have popularized and facilitated the use of geographical information on a variety of computational applications has been the use of Web maps; this has opened new research challenges on different subjects, from locating places and people, the study of social behavior or the analyzing of the hidden structures of the terms used in a natural language query used for locating a place. However, the use of geographic information under technological features is not new, instead it has been part of a development and technological integration process. This paper presents a state of the art review about the application of geographic information under different approaches: its use on location based services, the collaborative user participation on it, its contextual-awareness, its use in the Semantic Web and the challenges of its use in natural languge queries. Finally, a prototype that integrates most of these areas is presented
Knowledge Representation with Ontologies: The Present and Future
Recently, we have seen an explosion of interest in ontologies as
artifacts to represent human knowledge and as critical components in
knowledge management, the semantic Web, business-to-business
applications, and several other application areas. Various research
communities commonly assume that ontologies are the appropriate modeling
structure for representing knowledge. However, little discussion has
occurred regarding the actual range of knowledge an ontology can
successfully represent
Some Issues on Ontology Integration
The word integration has been used with different
meanings in the ontology field. This article
aims at clarifying the meaning of the word âintegrationâ
and presenting some of the relevant work
done in integration. We identify three meanings of
ontology âintegrationâ: when building a new ontology
reusing (by assembling, extending, specializing
or adapting) other ontologies already available;
when building an ontology by merging several
ontologies into a single one that unifies all of
them; when building an application using one or
more ontologies. We discuss the different meanings
of âintegrationâ, identify the main characteristics
of the three different processes and proposethree words to distinguish among those meanings:integration, merge and use
Knowledge society arguments revisited in the semantic technologies era
In the light of high profile governmental and international efforts to realise the knowledge society, I review the arguments made for and against it from a technology standpoint. I focus on advanced knowledge technologies with applications on a large scale and in open- ended environments like the World Wide Web and its ambitious extension, the Semantic Web. I argue for a greater role of social networks in a knowledge society and I explore the recent developments in mechanised trust, knowledge certification, and speculate on their blending with traditional societal institutions. These form the basis of a sketched roadmap for enabling technologies for a knowledge society
Supporting conceptualisation processes in collaborative networks: a case study on an R&D project
The development of new products or processes involves the creation, re-creation and integration of conceptual models from the related scientific and technical domains. Particularly, in the context of collaborative networks of organisations (CNO) (e.g. a multi-partner, international project) such developments can be seriously hindered by conceptual misunderstandings and misalignments, resulting from participants with different backgrounds or organisational cultures, for example. The research described in this article addresses this problem by proposing a method and the tools to support the collaborative development of shared conceptualisations in the context of a collaborative network of organisations. The theoretical model is based on a socio-semantic perspective, while the method is inspired by the conceptual integration theory from the cognitive semantics field. The modelling environment is built upon a semantic wiki platform. The majority of the article is devoted to developing an informal ontology in the context of a European R&D project, studied using action research. The case study results validated the logical structure of the method and showed the utility of the method
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