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Building a Knowledge Base with Data Crawled from Semantic Web

Publication at Faculty of Mathematics and Physics |
2011

Abstract

In this paper, we compare various approaches to semantic web data crawling. We introduce our crawling framework, which enables us to organize and clean the data before they are presented to the end user or used as a knowledge base.

We present methods of semantic data cleaning in order to keep the knowledge base consistent. We used the proposed framework to build a knowledge base containing data about persons crawled from semantic web data sources.

In this paper we present the results of the crawling process.