groupTime: preference based group scheduling Export

@inproceedings{citeulike:2860718, abstract = {As our business, academic, and personal lives continue to move at an ever-faster pace, finding times for busy people to meet has become an art. One of the most perplexing challenges facing groupware is effective asynchronous group scheduling (GS). This paper presents a lightweight interaction model for GS that can extend its reach beyond users of current group calendaring solutions. By expressing availability in terms of preferences, we create a flexible framework for GS that preserves plausible deniability while exerting social pressure to encourage honesty among users. We also propose an ontology that enables us to model user preferences with machine learning, predicting user responses to further lower cognitive load. The combination of visualization/direct manipulation with machine learning allows users to easily and efficiently optimize meeting times. We also suggest resulting design implications for this class of intelligent user interfaces.}, address = {New York, NY, USA}, author = {Brzozowski, Mike and Carattini, Kendra and Klemmer, Scott R. and Mihelich, Patrick and Hu, Jiang and Ng, Andrew Y.}, booktitle = {CHI '06: Proceedings of the SIGCHI conference on Human Factors in computing systems}, citeulike-article-id = {2860718}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1124929}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1124772.1124929}, doi = {10.1145/1124772.1124929}, isbn = {1-59593-372-7}, keywords = {groupware, intelligent\_user\_interfaces, plausible\_deniability, visualization}, location = {Montr\'{e}al, Qu\'{e}bec, Canada}, pages = {1047--1056}, posted-at = {2009-11-03 01:24:09}, priority = {0}, publisher = {ACM}, title = {groupTime: preference based group scheduling}, url = {http://dx.doi.org/10.1145/1124772.1124929}, year = {2006} }

TY - CONF ID - citeulike:2860718 L3 - citeulike-article-id:2860718 N2 - As our business, academic, and personal lives continue to move at an ever-faster pace, finding times for busy people to meet has become an art. One of the most perplexing challenges facing groupware is effective asynchronous group scheduling (GS). This paper presents a lightweight interaction model for GS that can extend its reach beyond users of current group calendaring solutions. By expressing availability in terms of preferences, we create a flexible framework for GS that preserves plausible deniability while exerting social pressure to encourage honesty among users. We also propose an ontology that enables us to model user preferences with machine learning, predicting user responses to further lower cognitive load. The combination of visualization/direct manipulation with machine learning allows users to easily and efficiently optimize meeting times. We also suggest resulting design implications for this class of intelligent user interfaces. CY - Montr\'{e}al, Qu\'{e}bec, Canada SN - 1-59593-372-7 AD - New York, NY, USA EP - 1056 TI - groupTime: preference based group scheduling PB - ACM T2 - CHI '06: Proceedings of the SIGCHI conference on Human Factors in computing systems SP - 1047 KW - groupware KW - intelligent_user_interfaces KW - plausible_deniability KW - visualization AU - Brzozowski, Mike AU - Carattini, Kendra AU - Klemmer, Scott AU - Mihelich, Patrick AU - Hu, Jiang AU - Ng, Andrew PY - 2006/// UR - http://dx.doi.org/10.1145/1124772.1124929 ER -