Recovering Damaged Documents to Improve Information Retrieval Processes

Although computer forensics is frequently related to the investigation of computer crimes, it can also be used in civil procedures. An example of case of use is information retrieval from damaged documents, where words have undergone alterations, either accidentally or intentionally. In this paper, we present a new tool able to retrieve information from large volumes of documents whose contents have been damaged. We have designed a new approach to recover the original words, composed of two stages: a text cleaning filter, able to remove non relevant information, and a text correction unit, which gather a general purpose spell checker with a N-gram based spell checker built specifically for the domain of the documents. The benefits of using this combined approach are two-fold: on the one hand, the general spell checker allows us to leverage all the general purpose techniques that are usually used to perform the corrections; on the other hand, the use of an N-gram based model allows us to adapt them to the particular domain we are tackling exploiting text regularities detected in successfully processed domain documents. The result of the correction allows us to improve automatic information retrieval tasks of from the texts. We have tested it using a real data set by using an information extraction tool based on semantic technologies in collaboration with the Spanish company InSynergy Consulting.