Artificial Intelligent Systems and Machine Learning

Sunitha Abburu ¹, G. Suresh Babu ¹

Affiliations
1 Dept. of Computer Applications, Adhiyamaan College of Engineering, Hosur, Tamilnadu, IN

Abstract

Ontology plays a vital role in semantic technologies. Ontology language is a formal languages used to build ontologies. Some of the popular ontology languages developed by different researchers are Ontolingua, OCML, LOOM, FLogic, SHOE, XOL, RDF(S), OIL, DAML+OIL, OWL and OWL2. This paper presents a detailed survey on ontology languages and their comparison. This survey article briefly describes the ontology languages and presents a comparison summary of the ontology languages with respect to their constructs and features. The comparison of the ontology languages help user to select a suitable language to implement an ontology in the domain of interest.

Keywords

Semantic Web, Ontology, Ontology Languages, Traditional Languages and Markup Languages.

Full Text

     

Sunitha Abburu ¹, G. Suresh Babu ²

Affiliations
1 Department of Computer Applications, Adhiyamaan College of Engineering, Tamilnadu, IN
2 Department of Computer Applications, Adhiyamaan College of Engineering, Hosur, Tamilnadu, IN

Abstract

Ontology plays a vital role in semantic web, knowledge engineering and information retrieval. The paper presents a comprehensive survey on ontology engineering methodologies. Ontology methodology is a set of procedures and guidelines derived from ontology development experiences. Some of the popular ontology methodologies are Sensus, Kactus, Uschold and King, Gruninger and Fox, Ontology development 101, Methontology, On-To-Knowledge, UPON, HCOME, DILIGENT, NeOn. This survey article describes the ontology engineering methodologies and it presents comparison summary of the ontology methodologies with respect to their features.

Keywords

Ontology, Ontology Development Process, Ontology Methodologies, Comparison of Ontology Methodologies.

Full Text

     

Sunitha Abburu ¹

Affiliations
1 Department of Computer Applications, Adhiyamaan College of Engineering, Hosur, Pin-635109, Tamilnadu, IN

Abstract

India is the world‘s largest producer of films. Music in Indian cinema is a substantial revenue generator. It makes up 72% of the music sales in India. Due to the rapid growth in technology the volume of music data is increasing day by day. Music lovers would like to listen to their choice of music based on the various semantic concepts. Most of the current MIR techniques refer to the low level features and text based annotation and retrieval techniques. Text based approaches do not serve the users requirements. As it is a known fact that there is a huge gap between the low level feature and the semantic concepts. User search is usually based on the semantic concepts. Ontology plays a vital role in semantic knowledge representation. The use of ontology in information retrieval enhances the performance of the retrieval system. The current research work focuses on the semantic knowledge identification and representation of Indian cinema music. As much work has not been done in this area this paper focuses on construction of a high level frame work of Indian cinema music ontology. The proposed method is been implemented using protégé. Conclusion and future work is been discussed at the end.

Keywords

Semantic Concepts, Ontology, Knowledge Representation, Cinema Music.

Full Text

     

Sunitha Abburu ¹

Affiliations
1 Department of Computer Applications, Adhiyamaan College of Engineering, Hosur-635109, Tamilnadu, IN

Abstract

Ontology is playing a vital role in semantic knowledge representation and semantic information retrieval. Ontologies are most widely used in artificial intelligence, semantic web, software engineering, information retrieval, knowledge representation, knowledge sharing, knowledge integration, knowledge reuse, and so on. Every academic year number of students and faculty devote their valuable time and effort in order to carry out the academic projects. The quality of education depends upon the quality of the projects students execute. The project details, knowledge representation, sharing and the semantic information retrieval are challenge issues. In this regard the project details and the associated project knowledge play a vital role. Various student academic project details and the associated information need to be well maintained. The project details and the associated semantic information needs to identified and represented to support project tracking, monitoring, controlling, tracing and semantic information retrieval. This in turn enhances the communication, understanding, effective knowledge sharing and learning. In this work, an ontology for the Graduate Student Academic Project (GSAP) is designed and implemented. The ontology provides efficient management and service provision of an intelligent GSAP management system.

Keywords

Semantic Concepts, Sub Ontology, Knowledge Representation, Academic Projects.

Full Text

     

Sunitha Abburu ¹

Affiliations
1 Department of Master of Computer Applications, Adhiyamaan College of Engineering, Hosur-635109, Tamilnadu, IN

Abstract

Video is most powerful, complex, voluminous, unformatted, and unstructured of all media used for conveying information. Hence, representing video information to enable effective and efficient video storage, semantic annotation, indexing and retrieval systems is an interesting problem. The current research is focusing on ontology based video annotation and retrieval, but most of the video systems focusing on one aspect of a particular domain. Not much research has been done on a comprehensive frame work for the identification of video semantic concept classes, classification of the video semantic concept classes and organizing concept hierarchies for generic video application. This paper proposes multiple sub ontologies for comprehensive video data base for any video applications. The proposed approach gives a comprehensive high level frame work for the identification of video concept classes, classification of the video concept classes and organizing concept hierarchies and classification of the concept instances. The beauty of the proposed approach is flexibility and generic which is applicable to any video application domain like sports, news, cinema, television programs, personalized video collections etc. multiple views of the video semantics are considered to build a comprehensive video system. Since a single ontology will not support the multiple views of the semantics of the video system. The multiple video concepts and the knowledge of the concepts and the concept hierarchies and the relationship between concepts are been addressed in multiple sub ontologies. The proposed model is been implemented using Protege tool. Finally conclusion and future work has been discussed.

Keywords

Comprehensive, Semantic Concepts, Sub Ontology, Video Data Base.

Full Text