In Ordinal Classification tasks, items have to be assigned to classes that have a relative ordering, such as “positive”, “neutral”, “negative” in sentiment analysis. Remarkably, the most popular evaluation metrics for ordinal classification tasks either ignore relevant information (for instance, precision/recall on each of the classes ignores their relative ordering) or assume additional information (for instance, Mean Average Error assumes absolute distances between classes). In this paper we propose a new metric for Ordinal Classification, Closeness Evaluation Measure, that is rooted on Measurement Theory and Information Theory. Our theoretical analysis and experimental results over both synthetic data and data from NLP shared tasks indicate that the proposed metric captures quality aspects from different traditional tasks simultaneously. In addition, it generalizes some popular classification (nominal scale) and error minimization (interval scale) metrics, depending on the measurement scale in which it is instantiated.

The importance of evaluation in promoting research and development in the information retrieval and natural language processing domains has long been recognised but is this sufficient? In many areas there is still a considerable gap between the results achieved by the research community and their implementation in commercial applications. This is particularly true for the cross-language or multilingual retrieval areas. Despite the strong demand for and interest in multilingual IR functionality, there are still very few operational systems on offer. The Cross Language Evaluation Forum (CLEF) is now taking steps aimed at changing this situation. The paper provides a critical assessment of the main results achieved by CLEF so far and discusses plans now underway to extend its activities in order to have a more direct impact on the application sector.

The objective of the Cross-Language Evaluation Forum (CLEF) is to promote research in the multilingual information access domain. In this short paper, we list the achievements of CLEF during its first four years of activity and describe how the range of tasks has been considerably expanded during this period. The aim of the paper is to demonstrate the importance of evaluation initiatives with respect to system research and development and to show how essential it is for such initiatives to keep abreast of and even anticipate the emerging needs of both system developers and application communities if they are to have a future.

We present a metagrammatical formalism, generic rules, to give a default interpretation to grammar rules. Our formalism introduces a process of dynamic binding interfacing the level of pure grammatical knowledge representation and the parsing level. We present an approach to non-constituent coordination within categorial grammars, and reformulate it as a generic rule. This reformulation is context-free parsable and reduces drastically the search space associated to the parsing task for such phenomena.