In the past, information was stored more or less well-structured in database. Nowadays, a lot of information is presented in unstructured format. The management of and retrieval from such large vast of textual information has been a challenging issue for organizations or individuals. Information extraction is the process of extracting relevant data from semi-structured or unstructured documents and transforming them into structured representations. Many information extraction learning techniques have been proposed. However, they are ineffectiveness on unstructured documents. Thus, in the research, we proposed a new information extraction learning algorithm, called LIEF, that enhancing existing information extraction learning techniques. According to the empirical evaluations on news documents that are unstructured format, the LIEF algorithm proposed showed its capabilities in accuracy rate.

<p>Danas, servisi e-Uprave u različitim oblastima koriste question answer sisteme koncepta u poku&scaron;aju da se razume tekst i da pomognu građanima u dobijanju odgovora na svoje upite u bilo koje vreme i veoma brzo. Automatsko mapiranje relevantnih dokumenata se ističe kao važna aplikacija za automatsku strategiju klasifikacije: upit-dokumenta. Ova doktorska disertacija ima za cilj doprinos u identifikaciji nestruktuiranih dokumenata i predstavlja važan korak ka razja&scaron;njavanju uloge eksplicitnih koncepata u pronalaženju podataka uop&scaron;te ajče&scaron; a reprezenta vna &scaron;ema u tekstualnoj kategorizaciji je BoW pristup, kada je u pozadini veliki skup znanja. Ova disertacija uvodi novi pristup ka stvaranju koncepta zasnovanog na tekstualnoj prezantaciji i primeni kategorizacije teksta, kako bi se stvorile definisane klase u slučaju sažetih tekstualnih dokumenata Takođe, ovde je prikazan algoritam zasnovan na klasifikaciji, modelovan za upite koji odgovaraju temi. Otežavaju a okolnost u slučaju ovog koncepta, koji prezentuje termine sa visokom frekvencijom pojavljivanja u upitma, zasniva se na sličnostima u prethodno definisanim klasama dokumenata Rezultati eksperimenta iz oblasti Krivičnog zakonika Republike Srbije, u ovom slučaju i studija, pokazuju da prezentacija teksta zasnovana na konceptu ima zadovoljavaju e rezultate i u slučaju kada ne postoji rečnik za datu oblast.</p> / <p>Nowadays, the concept of Question Answering Systems (QAS) has been used by e-government services in various fields as an attempt to understand the text and help citizens in getting answers to their questions promptly and at any time. Automatic mapping of relevant documents stands out as an important application for automatic classification strategy: query-document. This doctoral thesis aims to contribute to identification of unstructured documents and represents an important step towards clarifying the role of explicit concepts within Information Retrieval in general. The most common scheme in text categorization is BoW approach, especially when, as a basis, we have a large set of knowledge. This thesis introduces a new approach to the creation of text presentation based concept and applying text categorization, with the aim to create a defined class in case of compressed text documents.Also, this paper discusses the classification based algorithm modeled for queries that suit the theme. What makes the situation more complicated is the fact that this concept is based on the similarities in previously defined classes of documents and terms with a high frequency of appearance presented in queries. The results of the experiment in the field of the Criminal Code, and this paper as well, show that the text presentation based concept has satisfactory results even in case where there is no vocabulary for certain field.</p>