@conference {15318,
	title = {Question answering from the web using knowledge annotation and knowledge mining techniques},
	booktitle = {Proceedings of the twelfth international conference on Information and knowledge management},
	series = {CIKM {\textquoteright}03},
	year = {2003},
	month = {2003///},
	pages = {116 - 123},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {We present a strategy for answering fact-based natural language questions that is guided by a characterization of real-world user queries. Our approach, implemented in a system called Aranea, extracts answers from the Web using two different techniques: knowledge annotation and knowledge mining. Knowledge annotation is an approach to answering large classes of frequently occurring questions by utilizing semi\-structured and structured Web sources. Knowledge mining is a statistical approach that leverages massive amounts of Web data to overcome many natural language processing challenges. We have integrated these two different paradigms into a question answering system capable of providing users with concise answers that directly address their information needs.},
	keywords = {data-redundancy, semistructured data},
	isbn = {1-58113-723-0},
	doi = {10.1145/956863.956886},
	url = {http://doi.acm.org/10.1145/956863.956886},
	author = {Jimmy Lin and Katz,Boris}
}
