Researchers investigating personalization techniques for Web Information Retrieval face a challenge; that the data required to perform evaluations, namely query logs and click-through data, is not readily available due to valid privacy concerns. One option for researchers is to perform a user study, however, such experiments are often limited to small (and sometimes biased) samples of users, restricting somewhat the conclusions that can be drawn. Alternatively, researchers can look for publicly available data that can be used to approximate query logs and click-through data. Recently it has been shown that the information contained in social bookmarking (tagging) systems may be useful for improving Web search.
%0 Conference Paper
%1 citeulike:4618643
%A Carman, Mark J.
%A Baillie, Mark
%A Crestani, Fabio
%B SSM '08: Proceeding of the 2008 ACM Workshop on Search in Social Media
%C New York, NY, USA
%D 2008
%I ACM
%K adaptive-search information-retrieval tagging
%P 27--34
%R 10.1145/1458583.1458591
%T Tag data and personalized information retrieval
%U http://dx.doi.org/10.1145/1458583.1458591
%X Researchers investigating personalization techniques for Web Information Retrieval face a challenge; that the data required to perform evaluations, namely query logs and click-through data, is not readily available due to valid privacy concerns. One option for researchers is to perform a user study, however, such experiments are often limited to small (and sometimes biased) samples of users, restricting somewhat the conclusions that can be drawn. Alternatively, researchers can look for publicly available data that can be used to approximate query logs and click-through data. Recently it has been shown that the information contained in social bookmarking (tagging) systems may be useful for improving Web search.
%@ 978-1-60558-258-0
@inproceedings{citeulike:4618643,
abstract = {{Researchers investigating personalization techniques for Web Information Retrieval face a challenge; that the data required to perform evaluations, namely query logs and click-through data, is not readily available due to valid privacy concerns. One option for researchers is to perform a user study, however, such experiments are often limited to small (and sometimes biased) samples of users, restricting somewhat the conclusions that can be drawn. Alternatively, researchers can look for publicly available data that can be used to approximate query logs and click-through data. Recently it has been shown that the information contained in social bookmarking (tagging) systems may be useful for improving Web search.}},
added-at = {2018-03-19T12:24:51.000+0100},
address = {New York, NY, USA},
author = {Carman, Mark J. and Baillie, Mark and Crestani, Fabio},
biburl = {https://www.bibsonomy.org/bibtex/2909a636c42f0d831abbcdfc94d698050/aho},
booktitle = {SSM '08: Proceeding of the 2008 ACM Workshop on Search in Social Media},
citeulike-article-id = {4618643},
citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1458583.1458591},
citeulike-linkout-1 = {http://dx.doi.org/10.1145/1458583.1458591},
doi = {10.1145/1458583.1458591},
interhash = {2d7dc6f6b699a8d20b41cd49f62edf9d},
intrahash = {909a636c42f0d831abbcdfc94d698050},
isbn = {978-1-60558-258-0},
keywords = {adaptive-search information-retrieval tagging},
location = {Napa Valley, California, USA},
pages = {27--34},
posted-at = {2009-07-17 02:49:44},
priority = {2},
publisher = {ACM},
timestamp = {2018-03-19T12:24:51.000+0100},
title = {{Tag data and personalized information retrieval}},
url = {http://dx.doi.org/10.1145/1458583.1458591},
year = 2008
}