Y. Zhou, and W. Croft. Proceedings of the 14th ACM International Conference on Information and Knowledge Management, page 331--332. New York, NY, USA, ACM, (2005)
DOI: 10.1145/1099554.1099652
Abstract
The quality of document content, which is an issue that is usually ignored for the traditional ad hoc retrieval task, is a critical issue for Web search. Web pages have a huge variation in quality relative to, for example, newswire articles. To address this problem, we propose a document quality language model approach that is incorporated into the basic query likelihood retrieval model in the form of a prior probability. Our results demonstrate that, on average, the new model is significantly better than the baseline (query likelihood model) in terms of precision at the top ranks.
%0 Conference Paper
%1 zhou2005document
%A Zhou, Yun
%A Croft, W. Bruce
%B Proceedings of the 14th ACM International Conference on Information and Knowledge Management
%C New York, NY, USA
%D 2005
%I ACM
%K document ir model quality web
%P 331--332
%R 10.1145/1099554.1099652
%T Document quality models for web ad hoc retrieval
%U http://doi.acm.org/10.1145/1099554.1099652
%X The quality of document content, which is an issue that is usually ignored for the traditional ad hoc retrieval task, is a critical issue for Web search. Web pages have a huge variation in quality relative to, for example, newswire articles. To address this problem, we propose a document quality language model approach that is incorporated into the basic query likelihood retrieval model in the form of a prior probability. Our results demonstrate that, on average, the new model is significantly better than the baseline (query likelihood model) in terms of precision at the top ranks.
%@ 1-59593-140-6
@inproceedings{zhou2005document,
abstract = {The quality of document content, which is an issue that is usually ignored for the traditional ad hoc retrieval task, is a critical issue for Web search. Web pages have a huge variation in quality relative to, for example, newswire articles. To address this problem, we propose a document quality language model approach that is incorporated into the basic query likelihood retrieval model in the form of a prior probability. Our results demonstrate that, on average, the new model is significantly better than the baseline (query likelihood model) in terms of precision at the top ranks.},
acmid = {1099652},
added-at = {2011-05-25T17:51:01.000+0200},
address = {New York, NY, USA},
author = {Zhou, Yun and Croft, W. Bruce},
biburl = {https://www.bibsonomy.org/bibtex/2d190feee02f804aea11f19979d3642b8/jaeschke},
booktitle = {Proceedings of the 14th ACM International Conference on Information and Knowledge Management},
doi = {10.1145/1099554.1099652},
interhash = {01264e5f48959d326724b405d3898337},
intrahash = {d190feee02f804aea11f19979d3642b8},
isbn = {1-59593-140-6},
keywords = {document ir model quality web},
location = {Bremen, Germany},
numpages = {2},
pages = {331--332},
publisher = {ACM},
series = {CIKM '05},
timestamp = {2014-07-28T15:57:31.000+0200},
title = {Document quality models for web ad hoc retrieval},
url = {http://doi.acm.org/10.1145/1099554.1099652},
year = 2005
}