Specialised neural network for learning synonyms and related concepts in large document collections

For very large document collections or high volume streams of documents, finding relevant documents is a major information filtering problem. One of the main types of information retrieval systems produces a word frequency measure estimated by some important parts of the document using neural network approaches. This paper reports a new network structure for this task. It is specialised considering the main difficulties of these kinds of applications, namely, the calculation time complexity. It will be pointed out that the calculation, hence, the learning time is much reduced applying the new algorithm, however, the result is significantly improved compared to the former approaches, which offer a possibility to increase the number of considered words, hence, improve the effectiveness of information filtering systems.