Journal of the American Society for Information Science
Performance issues and error analysis in an open-domain question answering system
ACM Transactions on Information Systems (TOIS)
Answering Imprecise Queries over Autonomous Web Databases
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Ordering the attributes of query results
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Structured retrieval for question answering
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A knowledge based method for the medical question answering problem
Computers in Biology and Medicine
Foundations of preferences in database systems
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Introduction to Information Retrieval
Introduction to Information Retrieval
Addressing ontology-based question answering with collections of user queries
Information Processing and Management: an International Journal
Search Engines: Information Retrieval in Practice
Search Engines: Information Retrieval in Practice
Answering approximate queries over autonomous web databases
Proceedings of the 18th international conference on World wide web
A sophisticated library search strategy using folksonomies and similarity matching
Journal of the American Society for Information Science and Technology
An improved hierarchical Bayesian model of language for document classification
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Indexing on semantic roles for question answering
IRQA '08 Coling 2008: Proceedings of the 2nd workshop on Information Retrieval for Question Answering
AQUA: A Closed-Domain Question Answering System
Information Systems Management
A Domain-Specific Question Answering System Based on Ontology and Question Templates
SNPD '10 Proceedings of the 2010 11th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing
Using word clusters to detect similar web documents
KSEM'06 Proceedings of the First international conference on Knowledge Science, Engineering and Management
A group recommender for movies based on content similarity and popularity
Information Processing and Management: an International Journal
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Taking advantage of the Web, many advertisements (ads for short) websites, which aspire to increase client's transactions and thus profits, offer searching tools which allow users to (i) post keyword queries to capture their information needs or (ii) invoke form-based interfaces to create queries by selecting search options, such as a price range, filled-in entries, check boxes, or drop-down menus. 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 Q for retrieving relevant ads, if they exist, (ii) identifies ads as answers that partially-match the requested information expressed in Q, if insufficient or no answers to Q can be retrieved, which are ordered using a similarity-ranking approach, and (iii) analyzes incomplete or ambiguous questions to perform the "best guess" in retrieving answers that "best match" the selection criteria specified in Q. CQAds is also equipped with a Boolean model to evaluate Boolean operators that are either explicitly or implicitly specified in Q, 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.