Knowledge Searching over BBS

Abstract

The purpose aims to adopt traits of community behavior for searching effectiveness in a Bulletin Board System (BBS). The improved searching algorithm is used to promote reusability on the existing research resource of BBS. There are three traits of community behavior, time trend, relative active members, and referential resources. These three parameters can be adjusted as knowledge filtering. Therefore, they can attain what learners intend to get easily. BBS provides a mediated communication in asynchronous practice while members in the BBS community transfer implicit knowledge to explicit knowledge. This explicit knowledge can be also shared among all members. As time goes by, more and more knowledge in BBS will be accumulated as pool of knowledge. The key algorithms adopted in this study are LCS (Longest Common Subsequence, LCS) and LCCS (Longest Common Consecutive Subsequence). The subject of this study is RAS was established for research project at National Kaohsiung Normal University. RAS is originally designed for promoting reusability of existing research resource among RAS’s members. The results of this study consist of (a). A weighted ranking algorithm by LCS and LCCS is developed to improve ranking by traditional database approach. (b). A multiple presentation on searching results is designed for knowledge retrieval with easier interfaces. The next experiment study for verify the effectiveness of this improved search will be conducted soon. Finally, the implications for future research are also discussed.