语义工程中的几个问题——以解决初级数学应用问题的人形机器人为例

Ping Zhu
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摘要

本文讨论了语义工程的工程模型、语义描述、基本算法、启发式解析和平台等问题。以类人数学应用问题求解为例,提出了语义实例聚合、子句为语义单元、公式变量标签匹配和空间搜索方法;采用场景语义描述框架对上下文语义进行描述,设计了包括分词链、场景框架数据库、公式知识库和解析规则数据库在内的公共数据池;建立了场景帧匹配、数据元素与公式变量对应、公式变量约束算法和求解运行机制等基本算法;实现了问题的通用语义描述和选择,开发了启发式求解的加速运行机制;建立了语义数据平台。最后,总结了类人机器人的一般语义思想,解决了主要的数学应用问题,并提出了下一步的改进方案。
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Several Problems of Semantic Engineering A Case Study of Humanoid Resolving the Primary Mathematics Application Problems
In this paper, the problems, such as engineering model, semantic description, basic algorithm, heuristic resolving and platform of semantic engineering are discussed. Taking the humanoid resolving of mathematical application problem as an example, the semantic instances’ aggregation, clause as semantic unit, formula variable's labels matching and space search methods are proposed; the scene's semantic description frame is used to describe context semantics, and the common data pool which includes the word segmentation chain, scene frame database, formula knowledge database and resolving rule database are designed; The basic algorithms such as scene frame matching, correspondence between data elements and formula variables, formula variable constraint algorithm and resolving operation mechanism are established; The common semantic description and selection of problems are realized, and the accelerated operation mechanism of heuristic resolving is also developed; The semantic data platform is built. Finally, the paper summarizes the general semantic ideas of humanoid resolving the primary mathematical application problems, and puts forward the next improvement plan.
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