Pivoted document length normalization
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Information retrieval as statistical translation
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
On Relevance, Probabilistic Indexing and Information Retrieval
Journal of the ACM (JACM)
Experimentation as a way of life: Okapi at TREC
Information Processing and Management: an International Journal - The sixth text REtrieval conference (TREC-6)
A vector space model for automatic indexing
Communications of the ACM
Document normalization revisited
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
A Linguistically Motivated Probabilistic Model of Information Retrieval
ECDL '98 Proceedings of the Second European Conference on Research and Advanced Technology for Digital Libraries
Language Modeling for Information Retrieval
Language Modeling for Information Retrieval
A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
Introduction to Information Retrieval
Introduction to Information Retrieval
A statistical approach to mechanized encoding and searching of literary information
IBM Journal of Research and Development
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Question Answering Systems (QAS) are an important research topic triggered and at the same time stimulated by the immense amount of texts available in digital form. As the quantity of natural language information increases, the necessity of new methods to precisely retrieve the exact information from massive textual databases becomes inevitable. Although QAS have already been well explored, there are still many aspects to be solved, particularly those which are language specific. The main goal of the research presented in this paper was to compare three proven information retrieval (IR) models in order to accurately determine the relevant documents which contain the correct answer to questions posed in Macedonian language. It was accomplished using a real-life corpus of lectures and related questions existing in our e-testing system. In order to compare the results, we designed a small system capable of learning the correct answer. We revealed that the modified vector space model is the most suitable for our collection. The results we obtained are promising and they encouraged us for further improvement adopting some of the existing IR models, or even proposing a new one.