🤖 AI Summary
This study addresses the disconnect between statistical methods and semantic causal logic in enterprise knowledge bases, which impedes the precise identification of business bottlenecks. To bridge this gap, we propose a novel framework that conceptualizes language as an independent dynamic information layer. By integrating probabilistic vector spaces with ontological modeling and grounding the approach in dynamical systems theory, we construct a multi-dimensional solution space mapping framework that deeply couples statistical features with semantic logic. This methodology significantly enhances both knowledge extraction efficiency and its adaptability to business processes. Furthermore, it enables the accurate localization and effective resolution of logical bottlenecks within operational workflows. Ultimately, this work establishes a new paradigm for optimizing complex cognitive decision-making in enterprise environments.
📝 Abstract
Based on an analysis of the role of language in thought and communication, this article proposes a new concept for designing corporate knowledge bases. The concept integrates the probabilistic vector space of a corporate vocabulary, reflect-ing industry specifics, subject focus, terminology, and culture, with traditional ontological modeling. This combination enables the efficient extraction of knowledge from accumulated corporate documents while strictly accounting for specific business processes. Consequently, this concept bridges statistical and semantic (cause-and-effect) methodologies. Furthermore, analyzing the projec-tions of probabilistic spaces and causal relationships can help identify bottlenecks in business logic. As a dynamic system, language functions as a separate, inde-pendent layer within the overall information architecture. Introducing a dynamic component into the probabilistic space of word distribution allows it to be mod-eled as a multidimensional solution space for various problem formulations. In this context, input data defining the problem conditions serve as control parame-ters for dynamic transformations.