Expert Knowledge-Based Apparel Recommendation Question and Answer System

Aiming at the lack of professional knowledge to guide apparel recommendation,an apparel recommendation method based on image design expert knowledge has been proposed.Then,apparel recommendation knowledge graphs have been created and a apparel recommendation question and answer(Q&A)system has been designed and implemented.The question templates in the apparel recommendation domain were defined,the task of recognizing the named entities of question sentences was completed by the Bi-directional encoder representations from transformer-Bi-directional long short-term memory-conditional random field(BERT-BiLSTM-CRF)model,and the question template with the highest matching degree to the user’s question was obtained by using term frequency-inverse document frequency(TF-IDF)algorithm.The corresponding cypher graph database query statement was generated to retrieve the knowledge graph for answers,and iFLYTEK’s voice application programming interface(API)was called to implement the Q&A.The experimental results have shown that the Q&A system has a high accuracy rate and application value in the field of apparel recommendations.

Extracting Knowledge from On-Line Forums for Non-Obstructive Psychological Counseling Q&A System

Psychological counseling Q&A system is enjoying a remarkable and increasing popularity in recent years. Knowledge base is the important component for such kind of systems, but it is difficult and time-consuming to construct the knowledge base manually. Fortunately, there emerges large number of Q&A pairs in many psychological counseling websites, which can provide good source enriching the knowledge base. This paper presents the method of knowledge extraction from psychological consulting Q&A pairs of on-line psychological counseling websites, which include keywords, semantic extension and word sequence. P-XML, which is the knowledge template based on XML, is also designed to store the knowledge. The extracted knowledge has been successfully used in our non-obstructive psychologycal counseling system, called P.A.L., and the experimental results also demonstrated the feasibility and effectiveness of our approach.

Template-based knowledge reuse method for generating high-speed railway virtual construction scenes

Virtual construction has become an important approach to the high-quality development of high-speed railways,but existing methods have problems such as low efficiency in generating virtual construction scenes and the inability to reuse construction knowledge.To support the rapid visual representation of multiple types of construction processes and construction methods,a template-based knowledge reuse method is proposed.The method includes using a component-based modeling mode to build body structure models of a high-speed railway project and generate a 3D scene;decomposing the construction process and building a construction process knowledge base;establishing joint linkage models of construction machinery and forming a construction method knowledge template;and fusing multiple types of information according to a time sequence to visualize the construction process.Based on the template-based knowledge reuse method,a prototype system was developed,and virtual construction experiments were carried out.The results show that this method achieves the reuse of construction knowledge at different levels including construction machinery level,construction method level,and work site level.Compared with animation software for virtual construction,this method improves the production efficiency by 87%.Moreover,this method can provide a multilevel knowledge reuse scheme for diversified virtual construction.

A template-based knowledge reuse method for generating multitype 3D railway scenes

Constructing 3D railway scenes helps improve the railway information construction ability and the comprehensive railway management level.However,the existing modeling methods have disadvantages such as low flexibility in scene configuration,weak extensibility of scene objects and poor reusability of modeling knowledge.To enable multitype 3D railway scenes to be automatically constructed,a template-based knowledge reuse method was proposed in this paper.First,based on parsing of modeling operation characteristics and modeling knowledge expression,a modeling knowledge template was designed to store modeling knowledge and modeling operations in a parameterized way.The contents of this template were described in terms of semantic information,geometric information,topologic information and reference system information,and the method for instantiating the modeling knowledge template was proposed.Second,a scene configuration template was designed to organize the instantiated modeling knowledge files and scene objects.By the use of a flexible tree structure,the scene configuration template enables extensibility of scene objects.Finally,the two types of templates were parsed in terms of scene organization,linear referencing information,geometric and topologic relationships,and semantic descriptions.In this way,different types of 3D railway scenes were generated automatically.After a prototype system was developed,experiments on automatic modeling of two 3D railway scenes were carried out to verify the template-based knowledge reuse method.The experimental results show that the proposed method can be used to generate multitype 3D railway scenes automatically.With this method,model combination can be configured,model types can be extended and modeling knowledge can be reused.

An Agent-Based Simulation Model of Knowledge Spillover Under the Influence of High-Speed Railway

The calculation for the influence of high-speed railway on knowledge spillover is based on the results of global instantaneous equilibrium in the mechanism explanation of knowledge spillover. In real production, the interaction between the high-speed railway and the regional innovation system is dynamic and local. In order to simulate the impact of high-speed railway on innovation activities in the time dimension, it is necessary to simulate scenarios under appropriate parameter assumptions. Based on the interaction of economic participants, a discrete evolutionary simulation model is established,which is helpful to predict and estimate the evolution of spatial effect of high-speed railway according to the theory of cellular automata. It is concluded that high-speed railway accelerates the formation of knowledge innovation industry cluster in the region in the process of regional knowledge innovation and evolution. Under the influence of high-speed railway, the node city will gradually evolve into a regional innovation center. By comparing the production evolution of knowledge innovation system with and without high-speed railway, the results show that high-speed railway has a more significant impact on knowledge spillover in higher knowledge privatization environment. Under the background of low labor migration rate, high-speed railway has increased the potential of regional innovation to external knowledge spillover. In the case of higher labor migration rate, the convergence rate of influence of high-speed railway on the concentration of innovation is faster.