- document fields used for index creation: all, except ICO codes and legal status information
- (number of) created indexes, index languages: one index for English lemmas, one index for French lemmas, one index for German lemmas and one index for concepts based on our terminological database GRISP
- document fields used for query generation: all textual content
- pre-processing of documents/topics: Parsing of all XML documents, representation of all the metadata in a MySQL database, normalization and cleaning of all inventor and applicant names, identification with our citation mining tool (GROBID) of the patents cited in the descriptions, tokenization based on rules depending on the language, part of speech tagging and lemmatization, a key-term extraction, concept tagging
- indexing, retrieving systems: Lemur for all indexes, Okapi BM25 for lemmas and concept index, Indri for queries based on extracted key-terms
- ranking model: BM25 & Indri, SVM re-ranking
- use of cross-language and language specific methods you’ve made use of: see above, multilingual terminological database
- any other notes of relevance to your work and this track: additional techniques and resources used this year are presented here:

GRISP: A Massive Multilingual Terminological Database for Scientific and Technical Domains. P. Lopez and Laurent Romary. Proceedings of the International conference on Language Resources and Evaluation (LREC), Malta, May 2010.

Automatic Extraction and Resolution of Bibliographical References in Patent Documents. P. Lopez. First Information Retrieval Facility Conference (IRFC), Vienna, May 2010. Published in H. Cunningham, A. Hanbury, and S. R\"uger (Eds.): IRFC 2010, LNCS 6107, pp. 120-135. Springer, Heidelberg (2010). 

Automatic Key Term Extraction from Scientiﬁc Articles in GROBID. P. Lopez and L. Romary. Semeval-2 Workshop. Uppsala, Sweden, 2010.
