This paper reports on the work that has been conducted

by Fraunhofer SCAI for Trec Chemistry

(Trec-Chem) track 2009. The team of Fraunhofer

SCAI participated in two tasks, namely Technology

Survey and Prior Art Search. The core of the framework

is an index of 1.2 million chemical patents provided

as a data set by Trec. For the technology

survey, three runs were submitted based on semantic

dictionaries and noun phrases. For the prior art

search task, several elds were introduced into the index

that contained normalized noun phrases, biomedical

as well as chemical entities. Altogether, 36 runs

were submitted for this task that were based on automatic

querying with tokens, noun phrases and entities

along with dierent search strategies.