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As a model for knowledge description and formalization, ontologies are widely used to represent user profiles in personalized web information gathering. However, when representing user profiles, many models have utilized only knowledge from either a global knowledge base or a user local information. In this paper, a personalized ontology model is proposed for knowledge representation and reasoning...
For most scientists, their research interests are dynamically changing all the time. Through an analysis of research interests, we find that all the changes are with some characteristics. Plus, the research interests in the dynamic changing process are not isolated, instead, they are interconnected as a whole to form a holistic structure. We introduce some measurement parameters to track and detect...
Cognitive Informatics (CI) is a transdisciplinary enquiry of computer science, information sciences, cognitive science, and intelligence science that investigates into the internal information processing mechanisms and processes of the brain and natural intelligence, as well as their engineering applications in cognitive computing. This paper summarizes the presentations of a set of 14 position papers...
Retrieving accurate information from the Web is a great challenge to users. The existing information retrieval systems are mostly term-based and thus need to be enhanced toward knowledge-based. User information needs need to be better captured in order to deliver personalized search results. In this paper, an ontology-based framework is proposed for capturing user information needs using a world knowledge...
The goal of an on-line ontology-based question-answering system is to automatically derive answers from ontology knowledge bases without demanding additional information or intervention from users. This paper focuses on the problem of automatically mapping the tokens of a question into OWL elements, as an important step towards the further construction of answers. This problem can be essentially viewed...
The traditional techniques rely on human effort to acquire training sets, which is expensive and inefficient. In this paper we present an alternative method to automatically acquire training sets without heavy investment of user efforts. The proposed method tends to fill a gap for effectiveness of using Web data in Web mining, and contributes to Web information gathering. The evaluation shows that...
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