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KMi Seminars
Mining Knowledge from Textual Databases: An Approach using Ontology-based Context Vectors
This event took place on Monday 31 January 2005 at 12:30

 
Alexandre Goncalves KMi, The Open University

The increase in research activities claim ways to discover patterns in order to understand the behavior of these activities as well as to manage the resources used to support them. In this paper we propose a semantic mining approach to knowledge discovery based on context vectors and ontology. The approach is illustrated using ontology and resumes from a Science & Technology database as inputs. The involved phases in the proposed model are described emphasizing preprocessing and pattern generation. The main contribution of this paper is the proposal of a semantic component toward data mining. Initial results show a suitable cluster generation in terms of number and quality. The approach produced better classification when comparing the generated clusters against a set of vectors representing knowledge areas.

 
KMi Seminars
 

Knowledge Management is...


Knowledge Management
Creating learning organisations hinges on managing knowledge at many levels. Knowledge can be provided by individuals or it can be created as a collective effort of a group working together towards a common goal, it can be situated as "war stories" or it can be generalised as guidelines, it can be described informally as comments in a natural language, pictures and technical drawings or it can be formalised as mathematical formulae and rules, it can be expressed explicitly or it can be tacit, embedded in the work product. The recipient of knowledge - the learner - can be an individual or a work group, professionals, university students, schoolchildren or informal communities of interest.
Our aim is to capture, analyse and organise knowledge, regardless of its origin and form and make it available to the learner when needed presented with the necessary context and in a form supporting the learning processes.