Summarizing Local Context to Personalize Global Web Search
P. Chirita, C. Firan, and W. Nejdl. Intl. CIKM Conference on Information and Knowledge Management, Arlington, Virginia, USA, 06-11.11.06, (2006)
Abstract
The PC Desktop is a very rich repository of personal information,
efficiently capturing user’s interests. In this paper we propose a
new approach towards an automatic personalization of web search
in which the user specific information is extracted from such local
desktops, thus allowing for an increased quality of user profiling,
while sharing less private information with the search engine. More
specifically, we investigate the opportunities to select personalized
query expansion terms for web search using three different desktop
oriented approaches: summarizing the entire desktop data, summarizing
only the desktop documents relevant to each user query,
and applying natural language processing techniques to extract dispersive
lexical compounds from relevant desktop resources. Our
experiments with the Google API showed at least the latter two
techniques to produce a very strong improvement over current web
search.
%0 Conference Paper
%1 ChiritaFiran+:CIKM06
%A Chirita, Paul Alexandru
%A Firan, Claudiu S.
%A Nejdl, Wolfgang
%B Intl. CIKM Conference on Information and Knowledge Management, Arlington, Virginia, USA, 06-11.11.06
%D 2006
%K 2006 from:markusjunker l3s lang:en nepomuk
%T Summarizing Local Context to Personalize Global Web Search
%U http://www.l3s.de/~firan/publications/Summarizing%20Local%20Context%20to%20Personalize%20Global%20Web%20Search.pdf
%X The PC Desktop is a very rich repository of personal information,
efficiently capturing user’s interests. In this paper we propose a
new approach towards an automatic personalization of web search
in which the user specific information is extracted from such local
desktops, thus allowing for an increased quality of user profiling,
while sharing less private information with the search engine. More
specifically, we investigate the opportunities to select personalized
query expansion terms for web search using three different desktop
oriented approaches: summarizing the entire desktop data, summarizing
only the desktop documents relevant to each user query,
and applying natural language processing techniques to extract dispersive
lexical compounds from relevant desktop resources. Our
experiments with the Google API showed at least the latter two
techniques to produce a very strong improvement over current web
search.
@inproceedings{ChiritaFiran+:CIKM06,
abstract = {The PC Desktop is a very rich repository of personal information,
efficiently capturing user’s interests. In this paper we propose a
new approach towards an automatic personalization of web search
in which the user specific information is extracted from such local
desktops, thus allowing for an increased quality of user profiling,
while sharing less private information with the search engine. More
specifically, we investigate the opportunities to select personalized
query expansion terms for web search using three different desktop
oriented approaches: summarizing the entire desktop data, summarizing
only the desktop documents relevant to each user query,
and applying natural language processing techniques to extract dispersive
lexical compounds from relevant desktop resources. Our
experiments with the Google API showed at least the latter two
techniques to produce a very strong improvement over current web
search.
},
added-at = {2006-11-14T11:28:02.000+0100},
author = {Chirita, Paul Alexandru and Firan, Claudiu S. and Nejdl, Wolfgang},
biburl = {https://www.bibsonomy.org/bibtex/2c69a56e52e17cb6b46d5593a514b7c04/nepomuk},
booktitle = {Intl. CIKM Conference on Information and Knowledge Management, Arlington, Virginia, USA, 06-11.11.06},
interhash = {2668e27a2ca91e208ef2887d74636e02},
intrahash = {c69a56e52e17cb6b46d5593a514b7c04},
keywords = {2006 from:markusjunker l3s lang:en nepomuk},
timestamp = {2007-03-22T17:58:00.000+0100},
title = {Summarizing Local Context to Personalize Global Web Search},
url = {http://www.l3s.de/~firan/publications/Summarizing%20Local%20Context%20to%20Personalize%20Global%20Web%20Search.pdf},
year = 2006
}