# A Business-Model-Driven Approach to Task-Planning Knowledge Graph Construction
## 4 Model and Algorithm
### Representation Methods for Multidimensional Task-Planning Ontology Networks  
The ontology provides a unified conceptual definition, structural framework, and semantic rules for the knowledge graph, which is the key foundation for ensuring the quality and practicality of the knowledge graph [23]. There are two ways to build an ontology: top-down and bottom-up. Most domain knowledge graph ontology construction uses a top-down approach. This method relies too heavily on the subjective experience and assumptions of experts and lacks consideration of data from the real world, resulting in an ontology that differs greatly from the real world. Meanwhile, the lack of participation of practitioners in the domain has resulted in certain limitations in the knowledge coverage. The multi-dimensional task-planning ontology network expression method provides an a priori expression model for constructing a task-planning ontology network. It structurally divides and models task-planning knowledge from an ontological perspective, solving problems, such as the top-down construction method being too reliant on experts' subjective experience and assumptions, and lacking consideration of real-world data. The multi-dimensional task-planning ontology network expression method divides task-planning knowledge into five categories from an ontological perspective: task, resource, process, goal, and result. Each major category of knowledge is further subdivided into three levels according to the granularity of knowledge, corresponding to the macro, meso, and micro levels. Meanwhile, the method is based on the concept of the thinking chain in cognitive science [24], and each level of granularity of knowledge is characterized according to the three dimensions of structure, behavior, and function. The model structure of this expression method is shown in Figure 2.  
Figure 2: The model of representation methods for multidimensional task-planning ontology networks. Figure 3 shows a multi-dimensional expression model for task knowledge in the task-planning domain. First, the task knowledge in the planning domain is divided into three levels according to granularity: multi-tasks, subtasks, and meta-tasks. Then, the dependency between tasks of different granularities is defined to characterize the knowledge structure of the task category; the logical temporal relationship between different tasks of the same granularity is defined to characterize the knowledge behavior of the task category. The logical temporal relationship is expressed by the 13 types of relationships between time periods proposed by [PERSON] (2018); the functional description of each task category is defined to characterize the knowledge function of the task category. The functional description includes the task identity description, the task resource requirement description, and the task attribute description. Figure 4 shows a multi-dimensional expression model for resource knowledge in the task-planning domain. First, the resource knowledge in the planning domain is divided into three levels according to granularity: global resources, partitioned resources, and unit resources. Then, the unit resources are divided into three types of knowledge: resource entity, resource available fragment, and resource mode or type for description, and the composition relationship between resources of different granularities is defined to achieve the characterization of resource class knowledge structure; then, the association between the three types of knowledge in the description unit resource to characterize the behavior of the resource type knowledge and the functional description of the three types of knowledge in the description unit resource to characterize the function of the task-related knowledge are also defined. The functional description includes the attribute description of the resource entity, the attribute description of the available fragments of the resource, and the attribute description of the resource type or mode.