Tech Reports
Tech Report kmi-06-12 Abstract
Fusing automatically extracted annotations for the Semantic Web
Techreport ID: kmi-06-12
Date: 2006
Author(s): Andriy Nikolov
One of the necessary preconditions of the Semantic Web initiative is the availability of semantic data. The Web already contains large amounts of information intended for human users. This information is mainly stored as hypertext, which must be semantically annotated to make it accessible for software agents. The amount of information on the Web makes it impossible to solve the annotation task manually. Therefore the use of automatic information extraction algorithms is essential. These algorithms use various NLP and machine learning techniques to extract information from text. The information extracted from different sources must then be integrated in a knowledge base, so that it can be queried in a uniform way. This integration process is called knowledge fusion. However, performing knowledge fusion encounters a number of problems. The origins of these problems are the following: 1. Inaccuracy of existing information extraction algorithms leads to appearance of incorrect annotations. 2. Information contained on the web pages can be imprecise, incomplete or vague. 3. Multiple sources can contradict each other. Thus, in order to perform large-scale automatic annotation it is necessary to implement a knowledge fusion procedure, which is able to deal with these problems. Existing studies, which deal with the fusion issue, are either focused on solving separate subtasks of the problem or are only limited to a specific domain. The goal of this project is to make a contribution into the Semantic Web research by proposing a generic fusion framework based, which will make possible combining existing methods in order to perform knowledge fusion in a domain-independent way.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Semantic Web and Knowledge Services is...
Our research in the Semantic Web area looks at the potentials of fusing together advances in a range of disciplines, and applying them in a systemic way to simplify the development of intelligent, knowledge-based web services and to facilitate human access and use of knowledge available on the web. For instance, we are exploring ways in which tnatural language interfaces can be used to facilitate access to data distributed over different repositories. We are also developing infrastructures to support rapid development and deployment of semantic web services, which can be used to create web applications on-the-fly. We are also investigating ways in which semantic technology can support learning on the web, through a combination of knowledge representation support, pedagogical theories and intelligent content aggregation mechanisms. Finally, we are also investigating the Semantic Web itself as a domain of analysis and performing large scale empirical studies to uncover data about the concrete epistemologies which can be found on the Semantic Web. This exciting new area of research gives us concrete insights on the different conceptualizations that are present on the Semantic Web by giving us the possibility to discover which are the most common viewpoints, which viewpoints are mutually inconsistent, to what extent different models agree or disagree, etc...
Our aim is to be at the forefront of both theoretical and practical developments on the Semantic Web not only by developing theories and models, but also by building concrete applications, for a variety of domains and user communities, including KMi and the Open University itself.
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