Click any topic, and related documents are highlighted in the left-hand window. This often yields articles that the initial query missed. And in a further twist, groups of documents can be selected, indexed for keywords, and run against other literature databases to find related papers. Collexis, a Dutch firm based in The Hague, has taken this approach further by developing algorithms that can analyse documents not just for keywords but for 'concepts'. Taking its guide from thesauri such as the US National Library of Medicine's Unified Medical Language System, which recognizes more than 600,000 different biomedical concepts, Collexis's engine looks for defined patterns of terms and analyses their contextual relationships.
Users can paste any text, such as a scientific paper, into a search box.
This is automatically analysed to identify its major concepts, creating a profile that is then used to search for similar texts. Collexis also allows users to fine-tune their searches by adjusting the weighting given to each individual concept. Because the Collexis engine's concept matching does not depend on a document's precise grammatical structure, it can generate concepts for texts in many languages, based on a rough machine translation of a document's keywords. Indeed, the software was developed as part of a European Union-funded project to facilitate international cooperation between health researchers. Autonomy, a San Francisco-based company, is also using concepts.