Due to the specifics of different sports, actions from chosen sports will be considered in the research.
To model the fuzzy knowledge of the domain and temporal relations a knowledge representation scheme will be defined based on the theory of timed and fuzzy Petri nets or a similar formalism. For interpretation of sequential actions into more complex activities a model will be developed based on sports domain, which has well-defined rules, a known structure and context and clear roles exist for athletes and others involved. The starting point for action detection are methods based on machi ne learning and features that describe the spatio-temporal dimensions of multimedia content. We propose a research in which methods for sports domain action detection and annotation in multimedia content would be developed. The importance of having an n-gram infrastructure for rapid breakthroughs in new application areas is also exemplified in the paper. Because of the reliance on a service in constant use, the Croatian n-gram system is a dynamic one, unique among the systems compared. This resulted in a system comparable in size to the largest n-gram systems of today. Contrary to the Google n-gram systems, where cutoff criteria were applied, our n-gram filtering is based on dictionary criteria. The service has already processed a corpus whose size exceeds the size of the Croatian web-corpus created in recent years. Instead of using the Web as the world's biggest text repository, our process of n-gram collection relies on the Croatian academic online spellchecker Hascheck, a language service publicly available since 1993 and popular worldwide. This paper presents an innovative and economic approach to large-scale n-gram system creation applied to the Croatian language case. Any attempt to derive such systems, aimed to accelerate the development of NLP applications for world minority languages, in the manner in which it has been done in the project, encounters many obstacles. Google's n-gram project brought recently big data benefits to several main world languages, like English, Chinese etc.