Approximative Indexierungstechnik für historische deutsche Textvarianten

Historical documents have specific properties which make life hard for traditional information retrieval techniques. The missing notion of orthography and a general high degree of variation in the phonetic-graphemic representation, as well as in derivational morphology obstruct the possibility to find documents upon the entry of a modern word as the search term. The following paper gives an overview of existing string approximation technologies as used in bioinformatics, but also of phonetic approximation algorithms. It proposes an architecture of combining both notions, while using Jörg Michael’ phonet program to deduct from graphemes to a phonetic representation and a levenshtein automaton to allow for fast approximative matching. The final part of the paper evaluates the suitability of the approach, while using the levenshtein algorithm in its non-automaton-based implementation

Techniques for Automatic Normalization of Orthographically Variant Yiddish Texts

Yiddish is characterized by a multitude of orthographic systems. A number of approaches to automatic normalization of variant orthography have been explored for the processing of historic texts of languages whose orthography has since been standardized. However, these approaches have not yet been applied to Yiddish. Using a manually normalized set of 16 Yiddish documents as a training and test corpus, four techniques for automatic normalization were compared: a hand-crafted set of transformation rules, an off-the-shelf spell checker, edit distance minimization with manually set weights, and edit distance minimization with weights learned through a training set. Performance was evaluated by calculating the proportion of correctly normalized words in a test set, and by measuring precision and recall in a test of information retrieval. For the given test corpus, normalization by minimization of edit distance with multi-character edit operations and learned weights was found to perform best in all tests

Application of a POS Tagger to a Novel Chronological Division of Early Modern German Text

This paper describes the application of a part-of-speech tagger to a particular configuration of historical German documents. Most natural language processing (NLP) is done on contemporary documents, and historical documents can present difficulties for these tools. I compared the performance of a single high-quality tagger on two stages of historical German (Early Modern German) materials. I used the TnT (Trigrams 'n' Tags) tagger, a probabilistic tagger developed by Thorsten Brants in a 2000 paper. I applied this tagger to two subcorpora which I derived from the University of Manchester's GerManC corpus, divided by date of creation of the original document, with each one used for both training and testing. I found that the earlier half, from a period with greater variability in the language, was significantly more difficult to tag correctly. The broader tag categories of punctuation and "other" were overrepresented in the errors.Master of Science in Information Scienc

Temporal search in web archives

Web archives include both archives of contents originally published on the Web (e.g., the Internet Archive) but also archives of contents published long ago that are now accessible on the Web (e.g., the archive of The Times). Thanks to the increased awareness that web-born contents are worth preserving and to improved digitization techniques, web archives have grown in number and size. To unfold their full potential, search techniques are needed that consider their inherent special characteristics. This work addresses three important problems toward this objective and makes the following contributions: - We present the Time-Travel Inverted indeX (TTIX) as an efficient solution to time-travel text search in web archives, allowing users to search only the parts of the web archive that existed at a user's time of interest. - To counter negative effects that terminology evolution has on the quality of search results in web archives, we propose a novel query-reformulation technique, so that old but highly relevant documents are retrieved in response to today's queries. - For temporal information needs, for which the user is best satisfied by documents that refer to particular times, we describe a retrieval model that integrates temporal expressions (e.g., "in the 1990s") seamlessly into a language modelling approach. Experiments for each of the proposed methods show their efficiency and effectiveness, respectively, and demonstrate the viability of our approach to search in web archives.Webarchive bezeichnen einerseits Archive ursprünglich im Web veröffentlichter Inhalte (z. B. das Internet Archive), andererseits Archive, die vor langer Zeit veröffentlichter Inhalte im Web zugreifbar machen (z. B. das Archiv von The Times). Ein gewachsenes Bewusstein, dass originär digitale Inhalte bewahrenswert sind, sowie verbesserte Digitalisierungsverfahren haben dazu geführt, dass Anzahl und Umfang von Webarchiven zugenommen haben. Um das volle Potenzial von Webarchiven auszuschöpfen, bedarf es durchdachter Suchverfahren. Diese Arbeit befasst sich mit drei relevanten Teilproblemen und leistet die folgenden Beiträge: - Vorstellung des Time-Travel Inverted indeX (TTIX) als eine Erweiterung des invertierten Index, um Zeitreise-Textsuche auf Webarchiven effizient zu unterstützen. - Eine neue Methode zur automatischen Umformulierung von Suchanfragen, um negativen Auswirkungen entgegenzuwirken, die eine fortwährende Terminologieveränderung auf die Ergebnisgüte beim Suchen in Webarchiven hat. - Ein Retrieval-Modell, welches speziell auf Informationsbedürfnisse mit deutlichem Zeitbezug ausgerichtet ist. Dieses Retrieval-Modell bedient sich in Dokumenten enthaltener Zeitbezüge (z. B. "in the 1990s") und fügt diese nahtlos in einen auf Language Models beruhenden Retrieval-Ansatz ein. Zahlreiche Experimente zeigen die Effizienz bzw. Effektivität der genannten Beiträge und demonstrieren den praktischen Nutzen der vorgestellten Verfahren