An Adapted Ontology Model for Web Information Gathering

For knowledge portrayal and formalization, ontologies are extensively used to represent user profiles in personalized web information gathering. When representing user profiles, many models have made use of only knowledge from either a global knowledge base or user local information. This paper is aimed at the simulation of mind maps representing the preferences, in a software system and thereby enhancing the efficiency of web information gathering for a person. An adapted ontology model is suggested for knowledge representation and reasoning over user profiles. This model uncovers ontological user profiles from both a world knowledge base and user local instance repositories which possess content based descriptors. Content based descriptors have through indication to the notions specified in a global knowledge base. The model gives valuable contributions to personalized ontology engineering and concept-based Web information gathering. The suggested knowledge-based model donates to improved designs of knowledge-based and personalized Web information gathering systems. A multidimensional method, Specificity is also offered to quantitatively examine these semantic relations in a single framework. Specificity (denoted spe) portrays a subject‟s hub on a given topic. This method intends to investigate the subjects and the strength of their relationships in ontology. The user information wants at the sentence level rather than the article level, and presented user profiles by the Conceptual Ontological Graph. From a world knowledge base, we make adapted ontologies by adopting user feedback on interesting knowledge.