Linguistics is just one aspect of the proper use of conceptual analysis. Conceptual Analysis frameworks also lend itself to database inferential problem solving, knowledge engineering, artificial intelligence, decision systems, data mining, and other information systems. Here, Sowa (1984) has described the area of knowledge engineering with emphasis on research in the field of Artificial Intelligence in order to make logical computational systems that closely imitate the human cognitive workings of the brain. Sowa (1984) gives several descriptions of how conceptual structures can help solve problems in information systems, knowledge systems, database semantics, and knowledge retrieval. While conceptual analysis proves indispensible in several of problems, however it does have some limitations where the computational system cannot mimic the human cognition entirely.
The chapter on Limits of Conceptualization presents several limitations of logic. Sowa (1984) explains how conceptual analysis and its rationale can develop logical arguments but later the same arguments may present a paradoxical contradiction in its own form. He also explains that while modern computational systems may be better at inferential findings that human cognition nevertheless they only form one fourth of the cycle.
The challenge, as Sowa (1984) himself recognizes, is to design more flexible and human-like systems that are able to cover their limitations through their cognitive capabilities. Since every scientific discipline arises from the observation of actual happenings of nature, these abstractions may ignore the impacts of other factors that have not been incorporated. Many topics are considered in isolation from their environments which can lead to an illogical conclusion. Therefore, limitations arise when logic is in its entirety without consideration that logic itself is inclusive in a system of learning, and rationale.
As a result, a systematic approach is required in order to develop computational systems as human-like, in terms of cognition, as possible. On the whole, the conceptual architecture provided by Sowa (1984), which breaks down problems into sub parts allows logical deductions to be made. Conceptual analysis therefore is helpful particularly the cognitive graph notations in visualizing and reasoning cognitive processes. Many a times, there are no theories to help where analogies may prove useful. But to have a greater understanding of logic, database inference, and knowledge engineering, knowledge of artificial intelligence and cognitive abilities will be useful.
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