Hierarchy Database Lexicon Solution for Sentiments Challenge

Analyzing online sentiments challenges become hot research area to improve the accuracy and ease to understand. There are theoretical and technical sentiment challenges. World knowledge interprets old knowledge and updatable information.  Till now, a few research in this challenge, because of the hardness of it and no standard measurement for it. This challenge clearly appears in two issues: recent events or linguistics similarities.  This paper presents a new lexicon which is a solution for handling world knowledge challenge. This lexicon relies on a hierarchy database model. This research presents a new relationship between a topic domain and world knowledge challenge.  Sentiment analysis plays a vital role in business decisions. Our target involves this importance in a scientific domain to support the researchers. The experiment concentrates on linguistics similarities and knowledge information not updatable. Its results achieve nearly 70%.