Information Retrieval from Software Bug Ontology Exploiting Formal Concept Analysis

Shubhra Goyal Jindal, Arvinder Kaur


Knowledge extraction and structuring is attaining importance in real world applications such as e-commerce, decision support, problem solving and semantic web. Extraction of knowledge from collection of text documents is based upon identification of semantic content. Ontology plays an important role in accessing and structuring information. Developing an ontology are at the core of new strategies which requires accurate domain knowledge. Identification of structural and logical concepts is a time-consuming process. This work presents an ontology-based retrieval approach, that visualizes and structure the data of software bug reports domain. It exploits formal concept analysis (FCA) to elicit conceptualizations from bug reports datasets and a hierarchical taxonomy is generated of extracted knowledge. A lattice diagram of concepts and relationships is constructed from concept-relationship matrix created by FCA. Ontology is constructed on fluent editor tool and knowledge is extracted with the help of small queries executed on a reasoner window. The proposed approach is evaluated on 21 bug reports of apache projects of jira repository. It can be concluded that information can be retrieved easily from ontology as compared to manual extraction of data.


Knowledge extraction, formal concept analysis, ontology, software bug reports, concept-lattice

Full Text: PDF