Improving Identification of Latent User Goals through Search-Result Snippet Classification
K. He, Y. Chang, and W. Lu. WI '07: Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, page 683--686. Washington, DC, USA, IEEE Computer Society, (2007)
DOI: http://dx.doi.org/10.1109/WI.2007.137
Abstract
In this paper, we propose an enhanced approach to improving our previous method which employs syntactic structures (verb-object pairs) to identify latent user goals. Our new approach employs a supervised-learning method to learn hint verbs and considers URL information and title information to classify snippets into three coarse categories, which are resource-seeking, informational, and navigational. Also, we propose three different models to identify three different categories of specific latent user goals from the classified snippets.
Description
Improving Identification of Latent User Goals through Search-Result Snippet Classification
%0 Conference Paper
%1 He07
%A He, Kuan-Yu
%A Chang, Yao-Sheng
%A Lu, Wen-Hsiang
%B WI '07: Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
%C Washington, DC, USA
%D 2007
%I IEEE Computer Society
%K QueryClassification WebSearchResults intent latent
%P 683--686
%R http://dx.doi.org/10.1109/WI.2007.137
%T Improving Identification of Latent User Goals through Search-Result Snippet Classification
%U http://portal.acm.org/citation.cfm?id=1331740.1331801&coll=GUIDE&dl=GUIDE
%X In this paper, we propose an enhanced approach to improving our previous method which employs syntactic structures (verb-object pairs) to identify latent user goals. Our new approach employs a supervised-learning method to learn hint verbs and considers URL information and title information to classify snippets into three coarse categories, which are resource-seeking, informational, and navigational. Also, we propose three different models to identify three different categories of specific latent user goals from the classified snippets.
%@ 0-7695-3026-5
@inproceedings{He07,
abstract = {In this paper, we propose an enhanced approach to improving our previous method which employs syntactic structures (verb-object pairs) to identify latent user goals. Our new approach employs a supervised-learning method to learn hint verbs and considers URL information and title information to classify snippets into three coarse categories, which are resource-seeking, informational, and navigational. Also, we propose three different models to identify three different categories of specific latent user goals from the classified snippets.},
added-at = {2008-09-08T13:08:41.000+0200},
address = {Washington, DC, USA},
author = {He, Kuan-Yu and Chang, Yao-Sheng and Lu, Wen-Hsiang},
biburl = {https://www.bibsonomy.org/bibtex/2656867150c9753f1cc7518c642db45b4/mkroell},
booktitle = {WI '07: Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence},
description = {Improving Identification of Latent User Goals through Search-Result Snippet Classification},
doi = {http://dx.doi.org/10.1109/WI.2007.137},
interhash = {6ecb8aafae6f85c33da855a5205927bb},
intrahash = {656867150c9753f1cc7518c642db45b4},
isbn = {0-7695-3026-5},
keywords = {QueryClassification WebSearchResults intent latent},
pages = {683--686},
publisher = {IEEE Computer Society},
timestamp = {2009-09-08T10:53:23.000+0200},
title = {Improving Identification of Latent User Goals through Search-Result Snippet Classification},
url = {http://portal.acm.org/citation.cfm?id=1331740.1331801&coll=GUIDE&dl=GUIDE},
year = 2007
}