There has been a growing recognition of the importance of community-wide evaluations for research in information technologies. The Text Analysis Conference is a series of workshops that provides the infrastructure for large-scale evaluation of Natural Language Processing technology.
TAC's mission is to support research within the Natural Language Processing community by providing the infrastructure necessary for large-scale evaluation of NLP methodologies. TAC's primary purpose is not competitive benchmarking; the emphasis is on advancing the state of the art through evaluation results. In particular, the TAC workshop series has the following goals:
A TAC cycle consists of a set tracks, areas of focus in which particular NLP tasks are defined. The tracks serve several purposes. First, tracks act as incubators to experiment with new research areas; the first running of a track often defines what the problem really is, and a track creates the necessary infrastructure (test collections, evaluation methodology, etc.) to support research on its tasks. The tracks also demonstrate the robustness of core NLP technology in that the same techniques are frequently appropriate for a variety of tasks. Finally, the tracks make TAC attractive to a broader community by providing tasks that match the research interests of more groups. The TAC advisory committee selects the set of tracks that will be run in a given year of TAC based on track proposals.
Comments to: tac-web [at] nist.gov (tac-web[at]nist[dot]gov)