MEASURING THE VARIATION IN TASK-NEEDS FOR KNOWLEDGE DELIVERY: A PROFILING VIA COLLABORATION TECHNIQUE

摘要：

Effective knowledge management (KM) in a knowledge-intensive working environment requires an understanding of workers information needs for tasks, (task-needs), so that they can be provided with appropriate codified knowledge (textual documents) when performing long-term tasks.This work proposes a novel profiling technique based on Implicit relevance feedback and collaborative filtering techniques that model workers task-needs.The proposed profiling method analyses variations in workers task-needs for topics (i.e., topic needs) In a topic taxonomy over time.Variations in the topic needs of similar workers are used to predict variations in a target workers topic needs and adjust his/her task profile accordingly.Experiment results suggest that considering variations in the topic needs of similar workers during the profile adaptation process is effective in improving the precision of document retrieval.

关键词： Adaptive task-profiling similar workers topic taxonomy variation in task-needs

作者: DUEN-REN LIU I-CHIN WU PEI-CHENG CHANG

作者单位: Institute of Information Management, National Chiao Tung University, HsinChu, Taiwan, ROC Department of Information Management, Fu-Jen Catholic University, Taipei, Taiwan, ROC

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 2339-2344

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）