Ontology population as algebraic information system processing based on multi-agent natural language text analysis algorithms

Abstract

The paper presents an approach to ontology population as operations with Scott information sys tem. The deducibility relation in the ontology population information system corresponds to rules of input data processing and ontology population. To implement an ontology population process, we suggest a multi agent approach based on natural language semantic analysis. In the proposed multi agent model, agents of the following two types interact: information agents corresponding to meaningful units of the information being retrieved and rule agents implementing population rules of the given ontology based on the semanticsyntactic model of the language.

Development of the algorithm of keyword search in the Kazakh language text corpus

“…The ontology method is often used to implement data classification and data relationship in semantic analysis in automated text processing [12]. In [13], a multi-agent approach with the interaction of two agents was considered: the first corresponds to significant units of extracted information and the second rule agent implementing replenishment of the given ontology based on the semantic-syntactic language model. The study [14] used semantic networks in the extraction and visualization of knowledge, verb graphs with relational graphs to implement first-order logic.…”

Using Multiple Semantic Measures for Coreference Resolution in Ontology Population

“…3. The main analysis module constructs objects, corresponding to instances of subject domain ontology, from the terms [4], and resolves coreference [6]. The input for this module is the terminological cover with the structural information from the segment cover, and the analysis rules which implement semantic and syntactic models and ontology population rules.…”

“…We use the proposed framework to improve our coreference resolution algorithm suggested in [6] for making the decision on the candidate admissibility, which is used in our general approach to text analysis and information extraction for populating subject domain ontology. In our approach, the following IE tasks are performed: the preliminary extraction of subject domain terms from a given text [14]; the segmentation of the text into formal and genre fragments (sentences, sections, headlines, etc) [22]; the construction of objects corresponding to instances of a subject domain ontology, from the terms [4] and the coreference resolution [6]; the lexical and syntactic disambiguation [5]; the update of the ontology with the processed objects (planned as future work). In our framework, the coreference resolution problem means detecting if some group of retrieved objects refers to the particular ontology instance.…”

An Approach to Verification of a Family of Multi- agent Systems for Conflict Resolution

“…Мотивацией нашей работы является задача разрешения неоднозначности в рамках задачи пополнения онтологий из данных, представленных текстами на естественном языке. В работе [7] мы описали алгоритмы анализа текста, порождающие систему информационных агентов, соответствующих экземплярам заданной онтологии и входным данным. Однако особенности естественного языка порождают неоднозначности при пополнении онтологий, и эти агенты предназначены их разрешать.…”