The online dissemination of datasets is becoming common practice within the archaeology domain. Since the legacy database schemas involved are often created on a per-site basis, cross searching or reusing this data remains difficult. Employing an integrating ontology, such as the CIDOC CRM, is one step towards resolving these issues. However, this has tended to require computing specialists wit...

Relation extraction is a key step in the problem of structuring natural language text. This paper demonstrates a multi-class classifier for relation extraction, constructed using the distant supervision approach, along with resources of the Semantic Web. In particular, the classifier uses a feature based on the class hierarchy of an ontology that, in conjunction with basic lexical features, imp...

In this paper we investigate unsupervised population of a biomedical ontology via information extraction from biomedical literature. Relationships in text seldom connect simple entities. We therefore focus on identifying compound entities rather than mentions of simple entities. We present a method based on rules over grammatical dependency structures for unsupervised segmentation of sentences ...

Our thesis proposal aims at integrating word similarity measures in pattern ranking for relation extraction bootstrapping algorithms. We note that although many contributions have been done on pattern ranking schemas, few explored the use of word-level semantic similarity. Our hypothesis is that word similarity would allow better pattern comparison and better pattern ranking, resulting in less ...

In this paper we present a technique to automatically extract semantic knowledge from legislative text. Instead of using pattern matching methods relying on lexico-syntactic patterns, we propose a technique which uses syntactic dependencies between terms extracted with a syntactic parser. The idea is that syntactic information are more robust than pattern matching approaches when facing length ...

The Semant ic Binary Relat ionship Model (SBRM) is a f i r s t -o rde r formal ism which combines an o rgan lsa t iona l l y s imple basis ( I . e . b inary re la t ionsh ips) with the capabi l i t ies of semant ic networks and logical Integri ty and deduct ion ru les. The aim Is to permit the ef f ic ient model l ing of pract ica l en terpr ises In a DBMS context , whi lst accommodating the re...

The literature on definitions of security based on causalitylike notions such as noninterference has used several distinct semantic models for systems. Early work was based on state-machine and traceset definitions; more recent work has dealt with definitions of security in two distinct process algebraic settings. Comparisons between the definitions has been carried out mainly within semantic f...

In this position paper, we present our work towards designing a Semantic Web languages-compatible representation for networked sensors. The representation, Entity Notation, is proposed to connect sensors to the Semantic Web. Entity Notation can express RDF and OWL ontology models in a uniform format. Meanwhile, it offers a lightweight alternative for sensors with limited computation and communi...

The task of relation extraction is to recognize and extract relations between entities or concepts in texts. Dependency parse trees have become a popular source for discovering extraction patterns, which encode the grammatical relations among the phrases that jointly express relation instances. State-of-the-art weakly supervised approaches to relation extraction typically extract thousands of u...

Retrieving data from diverse information sources is a problem faced by many organizations. Many of these information sources are databases where diierent schemas may represent the same basic concept in diierent ways. The problem that leads to this semantic heterogeneity is termed modelling variation. Current approaches limit the retrieval of related information from multiple sources, because th...