Ontology Learning and Semantic Annotation: a Necessary Symbiosis

Semantic annotation of text requires the dynamic merging of linguistically structured information and a ?world model?, usually represented as a domain-specific ontology. On the other hand, the process of engineering a domain-ontology through semi-automatic ontology learning system requires the availability of a considerable amount of semantically annotated documents. Facing this bootstrapping paradox requires an incremental process of annotation-acquisition-annotation, whereby domain-specific knowledge is acquired from linguistically-annotated texts and then projected back onto texts for extra linguistic information to be annotated and further knowledge layers to be extracted. The presented methodology is a first step in the direction of a full ?virtuous? circle where the semantic annotation platform and the evolving ontology interact in symbiosis. As a case study we have chosen the semantic annotation of product catalogues. We propose a hybrid approach, combining pattern matching techniques to exploit the regular structure of product descriptions in catalogues, and Natural Language Processing techniques which are resorted to analyze natural language descriptions. The semantic annotation involves the access to the ontology, semi-automatically bootstrapped with an ontology learning tool from annotated collections of catalogues

Multimedia Information Extraction in Ontology-based Semantic Annotation of Product Catalogues

The demand for efficient methods for extracting knowledge from multimedia content has led to a growing research community investigating the convergence of multimedia and knowledge technologies. In this paper we describe a methodology for extracting multimedia information from product catalogues empowered by the synergetic use and extension of a domain ontology. The methodology was implemented in the Trade Fair Advanced Semantic Annotation Pipeline of the VIKE-framework

Exploring host-pathogen interactions through genome wide protein microarray analysis

During bacterial pathogenesis extensive contacts between the human and the bacterial extracellular proteomes take place. The identification of novel host-pathogen interactions by standard methods using a case-by-case approach is laborious and time consuming. To overcome this limitation, we took advantage of large libraries of human and bacterial recombinant proteins. We applied a large-scale protein microarray-based screening on two important human pathogens using two different approaches: (I) 75 human extracellular proteins were tested on 159 spotted Staphylococcus aureus recombinant proteins and (II) Neisseria meningitidis adhesin (NadA), an important vaccine component against serogroup B meningococcus, was screened against ∼2300 spotted human recombinant proteins. The approach presented here allowed the identification of the interaction between the S. aureus immune evasion protein FLIPr (formyl-peptide receptor like-1 inhibitory protein) and the human complement component C1q, key players of the offense-defense fighting; and of the interaction between meningococcal NadA and human LOX-1 (low-density oxidized lipoprotein receptor), an endothelial receptor. The novel interactions between bacterial and human extracellular proteins here presented might provide a better understanding of the molecular events underlying S. aureus and N. meningitidis pathogenesis.</p