Linguistic-based Method Research Articles

Trends in Teaching Critical Reading in the Thai Context

This study identifies and reviews recent research on trends in teaching methods and teaching levels for teaching critical reading skills in Thailand. Thirteen relevant studies were analyzed, including academic documents and research published between 2011 and 2022. The data were organized into two categories including the teaching methods and teaching levels. The results revealed eight popular teaching methods for teaching critical reading skills, including literature-based instruction, the group reading strategy (GRS), the QUEST analysis method, the multimodal tasks method, the content and language integrated learning (CLIL) model, the program for international student assessment (PISA) reading literacy assessment method, the applied linguistic-based method, and the survey, question, read, recite, record, react, and review (SQ5R) method. Moreover, critical reading is taught at three levels in Thailand: the university level, secondary school level, and elementary school level. This study is for those interested in finding an appropriate method for teaching critical reading in the Thai context.

Integrating IFC and CityGML Model at Schema Level by Using Linguistic and Text Mining Techniques

There is a growing interest in the interoperability between building information models (BIM) and geographic information systems (GIS). BIM can provide rich information for the generation of a GIS model, while the analysis tools in GIS can be used by BIM applications, such as the management of material supply chains and site selection. A comprehensive integration of the BIM and GIS is critical for interoperability between the two domains. However, many integration methods including manual inspection of complex and heterogeneous model files are time-consuming and have weak generalisation capability. This paper proposes a new linguistic-based semantic mapping method that uses the letter trigram-based word hashing method (WHSMM) to construct the feature vector, and then maps the Industry Foundation Classes (IFC) and City Geography Markup Language (CityGML) schemas through text mining techniques at schema level. The semantic mapping precision and recall obtained using WHSMM are compared with those of another linguistic-based method. The mapping result shows that performance of WHSMM is superior to that of another method in most cases. Therefore, the mapping candidates of WHSMM are used to transform the IFC datasets into CityGML models. The transformation results show that most of mapping candidates of the WHSMM can be used to practical data integration. The semantic mapping method presented in this paper can help map the IFC and CityGML schemas by effectively reducing the search space of the manual mapping method.

From emotion to language: Application of a systematic, linguistic-based approach to design a food-associated emotion lexicon

In recent years, new emotion and feeling lexicons developed in different languages and cultures have led to interesting insights into food- and odor-elicited emotions. However, most of the applied methods were not very systematic and used preexisting word lists as a starting point. None of the lexicons was generated from a linguistic perspective using comprehensive actual language use data. The aim of the present two studies was to explore the nature of the most appropriate terms used to describe food-related emotions with a systematic, linguistic-based method. In the first study, we applied a novel, three-step approach to the German language by collecting actively used emotion words. The collection and identification step resulted in 272 candidate terms that have an emotional connotation. In an online survey, 222 German-speaking participants rated the relevance of these candidate words in relation to food products. The positive–negative–neutral categorization in the second study was aimed to characterize the 272 candidate words and to test for the occurrence of a hedonic asymmetry. The application of the novel approach in Study 1 was useful to identify 49 terms. The result indicates that German-speaking consumers actively use differentiated and evaluative words to describe food-evoked emotions. Up to 70% of these expressions were positive, confirming the occurrence of a hedonic asymmetry by means of a linguistic-based approach. The nature of our identified expressions differed, however, from preexisting lists, which may be attributed to divergences in the applied approaches or suggested cultural aspects. Overall, the novel, systematic and linguistic-based approach, and the designed German emotion lexicon tailored to the consumers’ active language use, are valuable tools to deepen our understanding of the role that emotions play in food consumption experiences.

Some linguistic methods of improving the quality of document retrieval on the internet

One of the problems of e-business is to find relevant documents for making correct decisions. The main problem of the Internet is the huge amount of documents, which makes it difficult to find the relevant ones, hence the importance of the methods allowing for improving the quality of document retrieval. We discuss some linguistic problems of document retrieval on the internet related to the following natural language phenomena: (1) morphological processes: e.g., takes, took, taken are grammar forms of take; (2) polysemy and homonymy: most words have several senses, e.g., bank is a financial institution, shore, bench, etc.; (3) non-linearity of syntactic relations: in the case of a query that contains word combinations, the words forming a word combination can be separated by other words in the documents. Some linguistic-based methods and strategies related to the discussed problems are proposed that improve the quality of document retrieval or show the necessity of application of linguistic methods.