Ranking and scoring semantic document annotation

Semantic web makes computer understands meaning of queries. This state-of-the-art technology will assist human in querying rich documents based on their intention. We define rich document as semantic document in terms of its knowledge, which contains exact statements and related statements. However, some of the search engines are lack of ranking and scoring features. In this paper, we modify FF-ICF algorithm to ranking and scoring semantic document annotation based on document richness. Later, we apply the modification algorithm into a research prototype retrieval engine, PicoDoc, to experiment its ability in ranking and scoring documents annotation. The result shows a modified FF-ICF with related spreading concept yields promising results in retrieving related annotated document.