Easy to Find: A Natural Language Query Processing System on Advertisements Using an Automatically Populated Database

Yiu-Kai Ng

Abstract: Many commercial websites, such as Target.com, which aspire to increase client’s transactions and thus profits, offer users easy-to-use pull-down menus and/or keyword searching tools to locate advertisements (ads for short) posted at their sites. These websites, however, cannot handle natural language queries, which are formulated for specific information needs and can only be processed properly by natural language query processing (NLQP) systems. We have developed a novel NLQP system, denoted AdProc, which retrieves database records that match information specified in ads queries on multiple ads domains. AdProc relies on an underlying database (DB), which contains pre-processed (ads) records that provides the source of answers to users’ queries. AdProc automates the process of populating a DB using online ads and answering user queries on multiple ads domains. Experimental results using ads queries collected through Facebook on a dataset of online ads extracted from Craigslist.org an

External IDs:dblp:conf/webist/Ng23