The research in CIR is concerned with the study of retrieval methods and algorithms as well as with their applications.


Development of the associative interaction information retrieval method. The associative algorithm is based on general generic network equation, and takes advantage of the varying nature of the links between documents. It was shown experimentally that its retrieval effectiveness overperforms that of classical methods. Applications using the associative method have been develeoped, they can be accessed from the CIR web site.


Development of the HAT technology. The HAT is a complex methodology allowing for the evaluation of retrieval effectiveness of retrieval applications both in vitro and in vivo. The HAT technology was applied to the ’measurement’ of the most popular Web search engines, and the NeuRadIR medical retrieval application.


Creation of a unified framework for the basic retrieval algorithms. A unified formal framework for the Boolean, vector space, probabilistic, associative, and PageRank retrieval methods was given. Thus, their application in practice has become more effective and controlable; also, their teaching has become more methodic.


Limits of effectiveness enhancement. It was shown, using the concept of effectiveness surface,  that precision, recall and fallout cannot be enhanced simultaneously at any desired extent, only between certain limits that do not depend on the specific retrieval algorithms used.


Entropy-based TDV. A method based on entropy was developed for the computation of term discrimination values. It was shown experimentally that this method overperformed the earlier space density method.


Hyperbolic information retrieval. A smilarity-based retrieval method was developed in the Cayley-Klein hyperbolic space. It was shown theoretically and experimentally that this method was equivalent to the cosine-based vector space model but yielded the same categoricity in less time complexity.


Representativeness of acronyms. A method to estimate the representativeness of acronyms on the Web was developed based on reliability theory. It was shown that the majority of the acronyms of Hungarian public institutions do not identify their own institution when used as queries in search engines.