Current Web search tasks require human intervention both to devise queries and to assess the retrieved resources. Although this type of processing is still adequate for searches returning a few hundred pages, it can't scale to the volume of information produced when enterprises couple the vast amount of data available on the Web with company documents and databases. Leveraging Semantic Web technologies, the QuestSemantics system uses agents to automate discovery, annotation, filtering and retrieval of information resources on the Internet and in intranets.
%0 Journal Article
%1 Tamma10intelligent
%A Tamma, Valentina
%D 2010
%J IEEE Intelligent Systems
%K v1205 ieee paper semantic web information retrieval search enterprise knowledge agent zzz.th.c4
%N 1
%P 84-88
%R 10.1109/MIS.2010.25
%T Semantic Web Support for Intelligent Search and Retrieval of Business Knowledge
%V 25
%X Current Web search tasks require human intervention both to devise queries and to assess the retrieved resources. Although this type of processing is still adequate for searches returning a few hundred pages, it can't scale to the volume of information produced when enterprises couple the vast amount of data available on the Web with company documents and databases. Leveraging Semantic Web technologies, the QuestSemantics system uses agents to automate discovery, annotation, filtering and retrieval of information resources on the Internet and in intranets.
@article{Tamma10intelligent,
abstract = {Current Web search tasks require human intervention both to devise queries and to assess the retrieved resources. Although this type of processing is still adequate for searches returning a few hundred pages, it can't scale to the volume of information produced when enterprises couple the vast amount of data available on the Web with company documents and databases. Leveraging Semantic Web technologies, the QuestSemantics system uses agents to automate discovery, annotation, filtering and retrieval of information resources on the Internet and in intranets.},
added-at = {2012-05-30T10:54:58.000+0200},
author = {Tamma, Valentina},
biburl = {https://www.bibsonomy.org/bibtex/232c3bb44440fef33448876c799bc12e4/flint63},
doi = {10.1109/MIS.2010.25},
file = {IEEE Digital Library:2010/Tamma10intelligent.pdf:PDF},
groups = {public},
interhash = {9e74f721ea22764582969396dbdc7198},
intrahash = {32c3bb44440fef33448876c799bc12e4},
issn = {1541-1672},
journal = {IEEE Intelligent Systems},
keywords = {v1205 ieee paper semantic web information retrieval search enterprise knowledge agent zzz.th.c4},
number = 1,
pages = {84-88},
timestamp = {2018-04-16T11:54:17.000+0200},
title = {Semantic Web Support for Intelligent Search and Retrieval of Business Knowledge},
username = {flint63},
volume = 25,
year = 2010
}