The technological advancements in computer networks have caused a explosion of digitally stored information. In particular, textual information is becoming increasingly available in electronic form. Finding text documents dealing with a certain topic is not a simple task. Users need tools to sift through non-relevant information and retrieve only pieces of information relevant to their needs. The traditional methods of information retrieval based on term frequency have somehow reached their limitations. The retrieval of documents based on the positions of search terms in a document has the potential of yielding improvements, because other terms in the environment where a search term appears are considered. However, the required additional analysis task makes position based methods slower than traditional methods, affecting the performance of the most user critical phase of the retrieval process. This thesis explores the possibility of extending traditional information retrieval systems with positional information in an efficient manner optimizing the retrieval performance by handling term positions at query evaluation time.