Hybrid technique for effective knowledge representation & a comparative study
This work addresses the problem of knowledge representation for AI systems, but it appears incremental as it builds on existing hybrid techniques without claiming major breakthroughs.
The paper tackles the challenge of creating intelligent systems by proposing a hybrid knowledge representation technique to handle incomplete, ambiguous, and uncertain information, and it compares this technique with others to assess effectiveness and optimism in providing confident answers.
Knowledge representation (KR) and inference mechanism are most desirable thing to make the system intelligent. System is known to an intelligent if its intelligence is equivalent to the intelligence of human being for a particular domain or general. Because of incomplete ambiguous and uncertain information the task of making intelligent system is very difficult. The objective of this paper is to present the hybrid KR technique for making the system effective & Optimistic. The requirement for (effective & optimistic) is because the system must be able to reply the answer with a confidence of some factor. This paper also presents the comparison between various hybrid KR techniques with the proposed one.