Domain-specific web search engines are effective tools for reducing the difficulty in acquiring information from the web. Existing methods for building domain-specific web search engines require human expertise or specific facilities. However, we can build a domain-specific search engine simply by adding domain specific keywords called "keyword spices" to the user's input query and forwarding it to a generalpurpose web search engine. Keyword spices can be effectively discovered from web documents using machine learning technologies. This paper will describe domain-specific web search engines that use keyword spices for locating cooking recipes, restaurants, and used cars. To fully automate the construction of domain-specific search engines, we also present trials of using web pages in an existing web directory as training examples
