From User Query to User Model and Back: Adaptive Relevance-Based Visualization for Information Foraging Export

@inproceedings{citeulike:2599800, abstract = {Adaptive information filtering is a promising tool for both casual Web news readers and professional intelligence analysts. Adaptive filtering augments the traditional query- or profile-based rankings provided by search engines. An interesting research challenge in this context is to offer users more control over the rankings by letting them mediate between the two extremes -- query- and profile-based rankings. To address this challenge, we developed an adaptive relevance-based visual exploration tool based on the VIBE (Visual Information Browsing Environment) visualization approach, which was previously developed at our School. This paper presents the rationale and functionality of this visual exploration tool and reports the results of its preliminary evaluation.}, author = {Ahn, Jae-Wook and Brusilovsky, Peter}, booktitle = {Web Intelligence, IEEE/WIC/ACM International Conference on}, citeulike-article-id = {2599800}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/WI.2007.4427177}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4427177}, doi = {10.1109/WI.2007.4427177}, journal = {Web Intelligence, IEEE/WIC/ACM International Conference on}, keywords = {adaptive\_support, adaptive\_systems}, pages = {706--712}, posted-at = {2008-05-08 11:48:59}, priority = {2}, title = {From User Query to User Model and Back: Adaptive Relevance-Based Visualization for Information Foraging}, url = {http://dx.doi.org/10.1109/WI.2007.4427177}, year = {2007} }

TY - CONF ID - citeulike:2599800 L3 - citeulike-article-id:2599800 N2 - Adaptive information filtering is a promising tool for both casual Web news readers and professional intelligence analysts. Adaptive filtering augments the traditional query- or profile-based rankings provided by search engines. An interesting research challenge in this context is to offer users more control over the rankings by letting them mediate between the two extremes -- query- and profile-based rankings. To address this challenge, we developed an adaptive relevance-based visual exploration tool based on the VIBE (Visual Information Browsing Environment) visualization approach, which was previously developed at our School. This paper presents the rationale and functionality of this visual exploration tool and reports the results of its preliminary evaluation. JF - Web Intelligence, IEEE/WIC/ACM International Conference on EP - 712 TI - From User Query to User Model and Back: Adaptive Relevance-Based Visualization for Information Foraging T2 - Web Intelligence, IEEE/WIC/ACM International Conference on SP - 706 KW - adaptive_support KW - adaptive_systems AU - Ahn, Jae-Wook AU - Brusilovsky, Peter PY - 2007/// UR - http://dx.doi.org/10.1109/WI.2007.4427177 ER -