@inproceedings{f9e74d8819944a3181cb51924f1cec44,
title = "Measuring the variation in task-needs for knowledge delivery: A profiling via collaboration technique",
abstract = "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 worker's 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.",
keywords = "Adaptive task-profiling, Similar workers, Topic taxonomy, Variation in task-needs",
author = "Duen-Ren Liu and Wu, {I. Chin} and Chang, {Pei Cheng}",
year = "2007",
month = dec,
day = "1",
doi = "10.1109/ICMLC.2007.4370536",
language = "English",
isbn = "142440973X",
series = "Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007",
pages = "2339--2344",
booktitle = "Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007",
note = "6th International Conference on Machine Learning and Cybernetics, ICMLC 2007 ; Conference date: 19-08-2007 Through 22-08-2007",
}