Cost-effective creation of specialized search engines

People increasingly use Web search engines to fill a wide variety of navigational, informational, and transactional needs. However, today's major search engines demonstrate poor precision when searching for specialized information (e.g., buying guides). Specialized search engines address this problem by assuming a specific information need and returning results according to that assumption. This leads to increased precision with simple queries. However, building a specialized search engine requires a high level of expertise combined with a significant development effort, making them very expensive. This thesis proposes a flexible, extensible architecture, and tools for building specialized search engines based on Iterative, Filtering Metasearch (IFM). With our framework, an advanced web developer or consultant can build a search engine that is specialized by document type within a few man-weeks of effort. Furthermore, we show how IFM can successfully be used and adapted to the broader context of building specialized search applications, and also discuss the limitations of applying IFM.