Machine learning, data mining, and the World Wide Web : design of special-purpose search engines

We present DEADLINER, a special-purpose search engine that indexes conference and workshop announcements, and which extracts a range of academic information from the Web. SVMs provide an efficient and highly accurate mechanism for obtaining relevant web documents. DEADLINER currently extracts speakers, locations (e.g. countries), dates, paper submission (and other) deadlines, topics, program committees, abstracts, and affiliations. Complex and detailed searches are possible on these fields. The niche search engine was constructed by employing a methodology for rapid implementation of specialised search engines. Bayesian integration of simple extractors provides this methodology, that avoids complex hand-tuned text extraction methods. The simple extractors exploit loose formatting and keyword conventions. The Bayesian framework further produces a search engine where each user can control each fields false alarm rate in an intuitive and rigorous fashion, thus providing easy-to-use metadata.