林宏勳

With the rapid growth of internet, community-based question-answering service has become one of the promising knowledge sharing models. Through the internet, community members may share knowledge via asking questions and providing answers. However, members who participate in this community service, usually can only search or browse the knowledge content of the community passively to obtain and share knowledge. Since it is not easy to fully realize the user's demand, there exist problems of searching inaccuracy and time consuming on content browsing, that makes the ineffectiveness of knowledge circulation, and thus limits the development of the new knowledge sharing model. The objective of this research is to develop an automatic content delivery mechanism for community-based question-answering services so as to promote the effectiveness of community-based learning. The objective can be obtained through (1) providing more accurate knowledge content using a content searching method via analyzing the semantic of the question asked by user, (2) delivering more suitable knowledge content based on user’s preference and expertise. The results of this research will improve the searching accuracy and browsing efficiency and consequently facilitate the knowledge sharing in community-based question-answering services.