The Role of Context in the Interpretation of Academic and Professional Communication

This paper deals w h he ain elements hat form part of academc and professional comunicaton, namely he role of context, he concepton of comunicaton tself, he discoursal academc strategies and conventons, and other notons such as background knowedge or comon shared knowedge. In the first secton, we focus our atenton on he relatonship between he context n which he ext unfolds and ts typology, i.e. he social environment and he functonal organisaton of anguage. Next, he role of context n cognion is highlighted, o contnue w h he nteracton of participants n he act of comunicaton and he analysis of he relatonship between comunicative ntenton, strategies and nterpretaton. Finally, we present various applcatons of nguistc context w h the cogniive interface

KNOWEDGE DEVELOPMENT WITHIN COMMUNITIES OF PRACTICE USING ORGANIZATIONAL LEARNING

Knowledge assets are a critical resource that can generate a competitive advantage for organizations. Generally, knowledge can be divided in explicit knowledge and tacit knowledge. Organizations focus on managing the explicit knowledge and also on capturing the tacit knowledge embedded in the individuals’ experiences. Knowledge development represents the main purpose of the knowledge management domain, in both research and applications. Through the interactions in social networks, community-based knowledge development and sharing have become very effective tools. In this context, more and more organizations are developing communities of practice as strategic tools for knowledge development and sharing within the organization and across organizational boundaries.communities of practice, knowledge development, knowledge sharing, organizational learning

EXPLOITING N-GRAM IMPORTANCE AND ADDITIONAL KNOWEDGE BASED ON WIKIPEDIA FOR IMPROVEMENTS IN GAAC BASED DOCUMENT CLUSTERING

This paper provides a solution to the issue: “How can we use Wikipedia based concepts in document\ud clustering with lesser human involvement, accompanied by effective improvements in result?” In the\ud devised system, we propose a method to exploit the importance of N-grams in a document and use\ud Wikipedia based additional knowledge for GAAC based document clustering. The importance of N-grams\ud in a document depends on several features including, but not limited to: frequency, position of their\ud occurrence in a sentence and the position of the sentence in which they occur, in the document. First, we\ud introduce a new similarity measure, which takes the weighted N-gram importance into account, in the\ud calculation of similarity measure while performing document clustering. As a result, the chances of topical similarity in clustering are improved. Second, we use Wikipedia as an additional knowledge base both, to remove noisy entries from the extracted N-grams and to reduce the information gap between N-grams that are conceptually-related, which do not have a match owing to differences in writing scheme or strategies. Our experimental results on the publicly available text dataset clearly show that our devised system has a significant improvement in performance over bag-of-words based state-of-the-art systems in this area