The Clef Ip track ran for the rst time within Clef 2009. The purpose of the track was twofold: to encourage and facilitate research in the area of patent retrieval by providing a large clean data set for experimentation; to create a large test collection of patents in the three main European languages for the evaluation of cross lingual information access. The track focused on the task of prior art search. The 15 European teams who participated in the track deployed a rich range of Information Retrieval techniques adapting them to this new speci c domain and task. A large-scale test collection for evaluation purposes was created by exploiting patent citations.

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In the context of creating large scale test collections, the present paper discusses methods of constructing a patent test collection for evaluation of prior art search. In particular, it addresses criteria for topic selection and identification of recall bases. These issues arose while organizing the CLEF-IP evaluation track and were the subject of an online discussion among the track's organizers and its steering committee. Most literature on building test collections is concerned with minimizing the costs of obtaining relevance assessments. CLEF-IP can afford to have large topics sets since relevance assessments are generated by exploiting existing manually created information. In a cost-benefit analysis, the only issue seems to be the computing time required by participants to run (tens or hundreds of) thousands of queries. This document describes the data sets and decisions leading to the creation of the CLEF-IP collection.

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Symbolic Computation is an area of computer science that after 20 years of initial research had its acme in the mid-1980s, when its many new algorithms were made available in "math systems for the masses" like Mathematica and Maple. Computational algebra and computational logic are the two main pillars on which this discipline is based. Currently, the field experiences a new blossom by the integration and combination of new numeric, algebraic, geometric and logic algorithms made available in new, interactive and easy-to-use versions of these systems combined with web services. Spectacular new applications are reported in areas so different as elementary particle physics, cryptography, and automated software generation. One of the most outstanding outcomes of Symbolic Computation is the recently born Wolfram Alpha system, fully programmed in Mathematical. The goal of this writing is to remind the Information Retrieval community of the chances and capabilities offered by Symbolic Computation.