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These search mechanisms, however, are inadequate, since they cannot be used to specify a natural-language query with rich syntactic and semantic content, which can only be handled by a question answering (QA) system. Furthermore, existing ads websites are incapable of evaluating arbitrary Boolean queries or retrieving partially-matched answers that might be of interest to the user whenever a user's search yields only a few or no results at all. In solving these problems, we present a QA system for ads, called CQAds, which (i) allows users to post a natural-language question<jats:italic>Q<\/jats:italic>for retrieving relevant ads, if they exist, (ii) identifies ads as answers that partially-match the requested information expressed in<jats:italic>Q<\/jats:italic>, if insufficient or no answers to<jats:italic>Q<\/jats:italic>can be retrieved, which are ordered using a<jats:italic>similarity-ranking<\/jats:italic>approach, and (iii) analyzes incomplete or ambiguous questions to perform the \"best guess\" in retrieving answers that \"best match\" the selection criteria specified in<jats:italic>Q<\/jats:italic>. CQAds is also equipped with a Boolean model to evaluate Boolean operators that are either<jats:italic>explicitly<\/jats:italic>or<jats:italic>implicitly<\/jats:italic>specified in<jats:italic>Q<\/jats:italic>, i.e., with or without Boolean operators specified by the users, respectively. CQAds is easy to use, scalable to all ads domains, and more powerful than search tools provided by existing ads websites, since its query-processing strategy retrieves relevant ads of higher quality and quantity. We have verified the accuracy of CQAds in retrieving ads on eight ads domains and compared its ranking strategy with other well-known ranking approaches.<\/jats:p>","DOI":"10.14778\/2078331.2078337","type":"journal-article","created":{"date-parts":[[2014,6,24]],"date-time":"2014-06-24T12:17:57Z","timestamp":1403612277000},"page":"217-228","source":"Crossref","is-referenced-by-count":3,"title":["Generating exact- and ranked partially-matched answers to questions in advertisements"],"prefix":"10.14778","volume":"5","author":[{"given":"Rani","family":"Qumsiyeh","sequence":"first","affiliation":[{"name":"Brigham Young University, Provo, Utah"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maria S.","family":"Pera","sequence":"additional","affiliation":[{"name":"Brigham Young University, Provo, Utah"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiu-Kai","family":"Ng","sequence":"additional","affiliation":[{"name":"Brigham Young University, Provo, Utah"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2011,11]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"crossref","first-page":"25","DOI":"10.3115\/1599081.1599085","volume-title":"COLING","author":"Allison B.","year":"2008"},{"key":"e_1_2_1_2_1","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1145\/1277741.1277802","volume-title":"ACM SIGIR","author":"Bilotti M.","year":"2007"},{"issue":"2","key":"e_1_2_1_3_1","article-title":"Question answering from frequently-asked question files: Experiences with the faq finder system","volume":"18","author":"Burke R.","year":"1997","journal-title":"AI Magazine"},{"key":"e_1_2_1_4_1","first-page":"39","volume-title":"ACL Workshop on QA in Restricted Domains","author":"Chung H.","year":"2004"},{"key":"e_1_2_1_5_1","volume-title":"Addison Wesley","author":"Croft W.","year":"2010"},{"key":"e_1_2_1_6_1","first-page":"395","volume-title":"ACM SIGMOD","author":"Das G.","year":"2006"},{"key":"e_1_2_1_7_1","unstructured":"P. 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