Synonymous Non-taxonomic Relations Extraction
نویسندگان
چکیده
Construction of ontology is a difficult task, expensive and time-consuming. Concept, taxonomy and nontaxonomic relations, are the three important components in the development of ontology. These three components are used to represent the whole domain texts. Currently, most of studies focused on extracting the concept, the taxonomic relationships and the non-taxonomic relationships within the scope of single sentence. In order to enrich the domain ontology, we introduced a method to extract the non-taxonomic relations by using the similarities of relations that exist in more than one sentence. The most appropriate predicate are used as a reference to relate between concepts that occur not only in the same sentence, but also in different sentences. Here, the proposed method was tested using a collection of domain texts that described electronic voting machine and are evaluated based on the standard information retrieval performance metrics, i.e. precision and recall.
منابع مشابه
Descoberta Automática de Relações Não-Taxonômicas a Partir de Corpus em Língua Portuguesa
Ontology construction is a complex process composed by extraction tasks for domain concepts, as well as taxonomic and non-taxonomic relations among concepts. The extraction of non-taxonomic relations is the most neglected task, specially for Portuguese texts. Therefore, this paper presents a proposal for extracting non-taxonomic relations from Portuguese texts represented by a list of concepts ...
متن کاملDiscovery of Non-Taxonomic Concept Pairs from Unstructured Text in Support of Ontology Learning
Ontology consists of concepts, taxonomic relations and non-taxonomic relations. The majority of the ontology learning tools focus on discovering concepts and taxonomic relations. Very little effort has been put on discovering non-taxonomic relations. In this paper, we present a concept correlation search framework to discover non-taxonomic concept pairs from unstructured text. Our framework fea...
متن کاملExtraction of non-taxonomic relations from texts to enrich a basic ontology
Manual construction of ontologies is an expensive and time consuming task because the professionals required for this task (i.e. domain specialists and knowledge engineers) usually are highly specialized. The fast and cheap ontology development is crucial for the success of knowledge based applications and the Semantic Web. Ontology learning provides automatic or semi-automatic processes for on...
متن کاملDiscovery of Lexical Entries for Non-taxonomic Relations in Ontology Learning
Ontology learning from texts has recently been proposed as a new technology helping ontology designers in the modelling process. Discovery of non–taxonomic relations is understood as the least tackled problem therein. We propose a technique for extraction of lexical entries that may give cue in assigning semantic labels to otherwise ‘anonymous’ relations. The technique has been implemented as e...
متن کاملLearning Fine-grained Relations from Chinese User Generated Categories
User generated categories (UGCs) are short texts that reflect how people describe and organize entities, expressing rich semantic relations implicitly. While most methods on UGC relation extraction are based on pattern matching in English circumstances, learning relations from Chinese UGCs poses different challenges due to the flexibility of expressions. In this paper, we present a weakly super...
متن کامل