Ranking Algorithm for Semantic Document Annotations

Abstract

Semantic annotation represents a metadata of the document based on domain ontology. The purpose of this paper is to develop a ranking algorithm for semantic document annotation and to evaluate its performance in the Semantic Web (SW) application. The evaluation is to compare the ranking algorithm against other algorithms. For the evaluation purpose, all the algorithms are applied into the SW application. The SW application is a research prototype retrieval engine, PicoDoc. The system framework of PicoDoc is based on OCAS2008 ontology. During the experimentation stage, a real-life dataset from news article corpus of ABC and BBC websites are selected. The experiment shows promising results in retrieving related information using the ranking algorithm.

Generation of Heterogeneous Semantic Annotations of XML Pages: A Multi-viewpoints Approach

“…Several approaches to semantic annotation of text have been developed, for example, Baumgartner et al [6], Carme et al [29], Ciravegna and Wilks [30], Davulcu et al [31], Euzenat [32], Hanndschuh et al [7], Petridis et al [33], Rahayu [8], Sitthisarn and Bahoh [9] and Uren et al [10]. These approaches are based on natural language processing to extract data categories.…”

“…Current work such as [6,7,8,9,10,11,46] constructs only a consensual annotation of a resource, using a single ontology. Other work that constructs only a consensual semantic annotation of a resource, such as [12,13,14,15], uses multiple ontologies, intending to obtain a 'bigger' ontology with a larger set of concepts.…”