Traditional information retrieval systems retrieve documents based on keyword based matching, thereby incapable to provide results according to user information needs. These systems do not consider the semantic relationships among the user query keywords, thus cannot interpret the query context accurately. Query Expansion technique enhances the performance of information retrieval process by expanding user query with relevant meaningful concepts. Ontology represents semantics of a domain, and emerges as an important resource for query expansion. In this paper, we propose a query expansion framework based on conceptual knowledge derived from ontology in the domain of computer science. The system prototype results show good average precision percentage of 89.2% over keyword based search.
Ontology engineering is an important aspect of semantic web vision to attain the meaningful representation of data. Although various techniques exist for the creation of ontology, most of the methods involve the number of complex phases, scenario-dependent ontology development, and poor validation of ontology. This research work presents a lightweight approach to build domain ontology using Entity Relationship (ER) model. Firstly, a detailed analysis of intended domain is performed to develop the ER model. In the next phase, ER to ontology (EROnt) conversion rules are outlined, and finally the system prototype is developed to construct the ontology. The proposed approach investigates the domain of information technology curriculum for the successful interpretation of concepts, attributes, relationships of concepts and constraints among the concepts of the ontology. The experts' evaluation of accurate identification of ontology vocabulary shows that the method performed well on curriculum data with 95.75% average precision and 90.75% average recall.
Data security and data preserve privacy had been an important area to a huge in recent years. However, rapid developments in collecting, analyzing, and using personal data had made privacy a very important issue. This thesis had addressed the problem the protect user data in the dataset from attacks internal and attacks external by using combination techniques between security technique, and privacy technique and data mining technique. The research objectives were to determine the privacy and security technique in suitable the dataset, and to implement the combination property with chosen and security technique in order to protect user data in the dataset and to validate by comparing result before and after apply privacy techniques in dataset using chosen data mining tool. The research methodology consists of three phases. the analysis phase, combination techniques phase, and results evaluating phase and for every phase has research objective.
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