Large scale analysis of web revisitation patterns Export

@inproceedings{citeulike:2719627, abstract = {Our work examines Web revisitation patterns. Everybody revisits Web pages, but their reasons for doing so can differ depending on the particular Web page, their topic of interest, and their intent. To characterize how people revisit Web content, we analyzed five weeks of Web interaction logs of over 612,000 users. We supplemented these findings by a survey intended to identify the intent behind the observed revisitation. Our analysis reveals four primary revisitation patterns, each with unique behavioral, content, and structural characteristics. Through our analysis we illustrate how understanding revisitation patterns can enable Web sites to provide improved navigation, Web browsers to predict users' destinations, and search engines to better support fast, fresh, and effective finding and re-finding.}, address = {New York, NY, USA}, author = {Adar, Eytan and Teevan, Jaime and Dumais, Susan T.}, booktitle = {CHI '08: Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems}, citeulike-article-id = {2719627}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1357054.1357241}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1357054.1357241}, doi = {10.1145/1357054.1357241}, isbn = {9781605580111}, keywords = {clicks, time}, pages = {1197--1206}, posted-at = {2009-05-08 14:00:13}, priority = {0}, publisher = {ACM}, title = {Large scale analysis of web revisitation patterns}, url = {http://dx.doi.org/10.1145/1357054.1357241}, year = {2008} }

TY - CONF ID - citeulike:2719627 L3 - citeulike-article-id:2719627 N2 - Our work examines Web revisitation patterns. Everybody revisits Web pages, but their reasons for doing so can differ depending on the particular Web page, their topic of interest, and their intent. To characterize how people revisit Web content, we analyzed five weeks of Web interaction logs of over 612,000 users. We supplemented these findings by a survey intended to identify the intent behind the observed revisitation. Our analysis reveals four primary revisitation patterns, each with unique behavioral, content, and structural characteristics. Through our analysis we illustrate how understanding revisitation patterns can enable Web sites to provide improved navigation, Web browsers to predict users' destinations, and search engines to better support fast, fresh, and effective finding and re-finding. SN - 9781605580111 AD - New York, NY, USA EP - 1206 TI - Large scale analysis of web revisitation patterns PB - ACM T2 - CHI '08: Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems SP - 1197 KW - clicks KW - time AU - Adar, Eytan AU - Teevan, Jaime AU - Dumais, Susan PY - 2008/// UR - http://dx.doi.org/10.1145/1357054.1357241 ER -