In this paper, the conceptual spaces of the diachronic semantic evolution of “gen” are constructed through the diachronic literature surveys, then the cross-dialect/language semantic maps are drawn as a tool to examine the rationality of the diachronic evolution. “Gen (跟)” is an action verb with the meaning of “following (跟隨)”, in Chinese history the dominant words with the semantic field of “following” have experienced the diachronic evolution of “cong (從)”, “sui (隨)” and “gen (跟)”. The development of these three words not only follows the law of parallel grammaticalization, but also each has its own feature. From the comparison diachronic and cross-dialect /language semantic map of the “following (跟隨)” meaning, it can be seen that, non-cognate words with family characteristics may also have the same semantic evolution. Some phenomena in the synchronic regional semantic maps that violate the “semantic map connectivity hypothesis”, may not be due to the complete lack of connection between the two nodes, but due to the choice of semantics of a specific symbolic form in the diachronic development.

In this paper, the semantic map model is adopted to study the diachronic evolution and synchronic regional characteristics of the Chinese Verbs “Dai (代)” and “Ti (替)” with the meaning of “substitution”. The semantic evolution of the Verbs “Dai (代)” and “Ti (替)” are complicated, including the evolution in both dialects and general language, which can be clearly shown in the semantic map model. In the general language, “Dai (代)” and “Ti” have different lexical semantic functions. “Dai” mainly has the verbs semantic functions of “substitution”, yet the newer word “Ti (替)” mainly has the grammatical function of “substitution”. In the dialect, the evolution of the two verbs in different regions are not consistent. In northern dialects, the newer word “Ti (替)” is mostly used, yet in some southern dialects, more components of the ancient Chinese are retained, such as the prepositional function of “Dai (代)” in ancient Chinese.

This paper analyzes the Korean conjunctives –ko and –ese, and the Turkish converb –Ip, which have various meanings, and reveals their similarities and differences visually using the semantic map model. –ko and –ese are learned at the beginner level but Turkish learners have shown many errors. Those two Korean conjunctives express different temporal meanings, however, the corresponding Turkish converb expressed them in a single form. Korean textbooks have introduced the meanings of –ko and –ese as [sequential] and [continuous], but it can be made more confusing for learners by presenting the meaning using the same term. Therefore, it is necessary to teach the meanings of the two connectives in more detail according to their syntactic characteristics. Since most textbooks of Korean do not clearly present the differences between the –ko and –ese, effective teaching methods for Turkish-speaking learners based on the Focus-on-Form approach are proposed. To teach the conjunctives –ko and –ese, distinguishing between features of different meanings and to recognize those differences is encouraged.

This paper describes hierarchical semantic map building using the classified area information in home environments. The hierarchical semantic map consists of a grid, CAIG (Classified Area Information in Grid), and topological map. The grid and CAIG maps are used for navigation and motion selection, respectively. The topological map provides the intuitive information on the environment, which can be used for the communication between robots and users. The proposed semantic map building algorithm can greatly improve the capabilities of a mobile robot in various domains, including localization, path-planning and HRI (Human-Robot Interaction). In the home environment, a door can be used to divide an area into various sections, such as a room, a kitchen, and so on. Therefore, we used not only the grid map of the home environment, but also the door information as a main clue to classify the area and to build the hierarchical semantic map. The proposed method was verified through various experiments and it was found that the algorithm guarantees autonomous map building in the home environment.