Modular ontologies and CBR-based hybrid system for web information retrieval

Increasing amounts of data volume used on the Web and their heterogeneous character make the search for information a challenging task. Several advanced computing methods and technologies propose to incorporate a degree of semantic analysis during the search based on ontologies. Ontology engineering is based on the methods and methodologies for building ontologies combined with engineering process. This paper proposes a hybrid system based on ontology engineering and aiming to enhance web information retrieval results, by combining automatic Modular Ontology building with CBR (CBRModOnto). The system integrates a novel dynamic composition approach of modular ontologies, performed to reorganize the overlapping concepts between the different ontology modules and updates their hierarchy using semantic similarity measure. The search in our system occurs in two main phases. The first one composes modular ontologies and manages the knowledge base, while the second phase manages the CBR process. A demonstration case study presents a scenario to illustrate the proposed system. Our system has been implemented, the obtained experimental results show that hybridization that we propose enables an improvement of query reformulation, predicted ranking score and user's satistaction.