Information Retrieval: A Case Study on Contributions of Greimasian Semiotics to Semantic Computing in Agriculture for Knowledge Management

This paper aims to discuss how a linguistic-discursive approach can contribute to semantic computing field, especially to information retrieval process. A brief history of devices and methods used to storage and share knowledge reveals different strategies that aim to optimize users' searches through increasingly fast and accurate answers. The modern data-intensive technologies, the increased computational, and the data storage resources knowledge, that can be shared and accessed instantly, demand new discussions about the contributions of language theories to information retrieval. For this, it is analyzed a document that composes an innovative platform of knowledge management in agriculture, applying concepts offered by Greimas and his group in order to extract relevant information that can support the search engines. This scientific project related to the study of meaning generation associated to knowledge domain, to semantic computing approach become to be an important tool to help in the search of computer science advances, especially for bringing about continuous improvement within organizations and making them more competitive.