Envisioning user models for adaptive visualization Export

@inproceedings{citeulike:3655426, abstract = {Adaptive search systems apply user models to provide better separation of relevant and non-relevant documents in a list of results. This paper presents our attempt to leverage this ability of user models in the context of visual information analysis. We developed an adaptive visualization approach for presentation and exploration of search results. We simulated a visual intelligence search/analysis scenario with log data extracted from an adaptive information foraging study and were able to verify that our method can improve the ability of traditional relevance visualization to separate relevant and irrelevant information.}, author = {Ahn, Jae-Wook and Brusilovsky, Peter}, booktitle = {Visual Analytics Science and Technology, 2008. VAST '08. IEEE Symposium on}, citeulike-article-id = {3655426}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/VAST.2008.4677373}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4677373}, doi = {10.1109/VAST.2008.4677373}, journal = {Visual Analytics Science and Technology, 2008. VAST '08. IEEE Symposium on}, keywords = {user\_model, vibe, visualization}, pages = {175--176}, posted-at = {2008-11-21 18:37:43}, priority = {2}, title = {Envisioning user models for adaptive visualization}, url = {http://dx.doi.org/10.1109/VAST.2008.4677373}, year = {2008} }

TY - CONF ID - citeulike:3655426 L3 - citeulike-article-id:3655426 N2 - Adaptive search systems apply user models to provide better separation of relevant and non-relevant documents in a list of results. This paper presents our attempt to leverage this ability of user models in the context of visual information analysis. We developed an adaptive visualization approach for presentation and exploration of search results. We simulated a visual intelligence search/analysis scenario with log data extracted from an adaptive information foraging study and were able to verify that our method can improve the ability of traditional relevance visualization to separate relevant and irrelevant information. JF - Visual Analytics Science and Technology, 2008. VAST '08. IEEE Symposium on EP - 176 TI - Envisioning user models for adaptive visualization T2 - Visual Analytics Science and Technology, 2008. VAST '08. IEEE Symposium on SP - 175 KW - user_model KW - vibe KW - visualization AU - Ahn, Jae-Wook AU - Brusilovsky, Peter PY - 2008/// UR - http://dx.doi.org/10.1109/VAST.2008.4677373 ER -