Spanish named entity recognition in the biomedical domain

Named Entity Recognition in the clinical domain and in languages different from English has the difficulty of the absence of complete dictionaries, the informality of texts, the polysemy of terms, the lack of accordance in the boundaries of an entity, the scarcity of corpora and of other resources available. We present a Named Entity Recognition method for poorly resourced languages. The method was tested with Spanish radiology reports and compared with a conditional random fields system.Peer ReviewedPostprint (author's final draft

Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems

Proceedings of the Workshop Semantic Content Acquisition and Representation (SCAR) 2007

This is the proceedings of the Workshop on Semantic Content Acquisition and Representation, held in conjunction with NODALIDA 2007, on May 24 2007 in Tartu, Estonia.</p

A stemming algorithm for Latvian

The thesis covers construction, application and evaluation of a stemming algorithm for advanced information searching and retrieval in Latvian databases. Its aim is to examine the following two questions: Is it possible to apply for Latvian a suffix removal algorithm originally designed for English? Can stemming in Latvian produce the same or better information retrieval results than manual truncation? In order to achieve these aims, the role and importance of automatic word conflation both for document indexing and information retrieval are characterised. A review of literature, which analyzes and evaluates different types of stemming techniques and retrospective development of stemming algorithms, justifies the necessity to apply this advanced IR method also for Latvian. Comparative analysis of morphological structure both for English and Latvian language determined the selection of Porter's suffix removal algorithm as a basis for the Latvian sternmer. An extensive list of Latvian stopwords including conjunctions, particles and adverbs, was designed and added to the initial sternmer in order to eliminate insignificant words from further processing. A number of specific modifications and changes related to the Latvian language were carried out to the structure and rules of the original stemming algorithm. Analysis of word stemming based on Latvian electronic dictionary and Latvian text fragments confirmed that the suffix removal technique can be successfully applied also to Latvian language. An evaluation study of user search statements revealed that the stemming algorithm to a certain extent can improve effectiveness of information retrieval

Beyond Stemming and Lemmatization: Ultra-stemming to Improve Automatic Text Summarization

In Automatic Text Summarization, preprocessing is an important phase to reduce the space of textual representation. Classically, stemming and lemmatization have been widely used for normalizing words. However, even using normalization on large texts, the curse of dimensionality can disturb the performance of summarizers. This paper describes a new method for normalization of words to further reduce the space of representation. We propose to reduce each word to its initial letters, as a form of Ultra-stemming. The results show that Ultra-stemming not only preserve the content of summaries produced by this representation, but often the performances of the systems can be dramatically improved. Summaries on trilingual corpora were evaluated automatically with Fresa. Results confirm an increase in the performance, regardless of summarizer system used.Comment: 22 pages, 12 figures, 9 table

Term-driven E-Commerce

Die Arbeit nimmt sich der textuellen Dimension des E-Commerce an. Grundlegende Hypothese ist die textuelle Gebundenheit von Information und Transaktion im Bereich des elektronischen Handels. Überall dort, wo Produkte und Dienstleistungen angeboten, nachgefragt, wahrgenommen und bewertet werden, kommen natürlichsprachige Ausdrücke zum Einsatz. Daraus resultiert ist zum einen, wie bedeutsam es ist, die Varianz textueller Beschreibungen im E-Commerce zu erfassen, zum anderen können die umfangreichen textuellen Ressourcen, die bei E-Commerce-Interaktionen anfallen, im Hinblick auf ein besseres Verständnis natürlicher Sprache herangezogen werden

Foundation, Implementation and Evaluation of the MorphoSaurus System: Subword Indexing, Lexical Learning and Word Sense Disambiguation for Medical Cross-Language Information Retrieval

Im medizinischen Alltag, zu welchem viel Dokumentations- und Recherchearbeit gehört, ist mittlerweile der überwiegende Teil textuell kodierter Information elektronisch verfügbar. Hiermit kommt der Entwicklung leistungsfähiger Methoden zur effizienten Recherche eine vorrangige Bedeutung zu. Bewertet man die Nützlichkeit gängiger Textretrievalsysteme aus dem Blickwinkel der medizinischen Fachsprache, dann mangelt es ihnen an morphologischer Funktionalität (Flexion, Derivation und Komposition), lexikalisch-semantischer Funktionalität und der Fähigkeit zu einer sprachübergreifenden Analyse großer Dokumentenbestände. In der vorliegenden Promotionsschrift werden die theoretischen Grundlagen des MorphoSaurus-Systems (ein Akronym für Morphem-Thesaurus) behandelt. Dessen methodischer Kern stellt ein um Morpheme der medizinischen Fach- und Laiensprache gruppierter Thesaurus dar, dessen Einträge mittels semantischer Relationen sprachübergreifend verknüpft sind. Darauf aufbauend wird ein Verfahren vorgestellt, welches (komplexe) Wörter in Morpheme segmentiert, die durch sprachunabhängige, konzeptklassenartige Symbole ersetzt werden. Die resultierende Repräsentation ist die Basis für das sprachübergreifende, morphemorientierte Textretrieval. Neben der Kerntechnologie wird eine Methode zur automatischen Akquise von Lexikoneinträgen vorgestellt, wodurch bestehende Morphemlexika um weitere Sprachen ergänzt werden. Die Berücksichtigung sprachübergreifender Phänomene führt im Anschluss zu einem neuartigen Verfahren zur Auflösung von semantischen Ambiguitäten. Die Leistungsfähigkeit des morphemorientierten Textretrievals wird im Rahmen umfangreicher, standardisierter Evaluationen empirisch getestet und gängigen Herangehensweisen gegenübergestellt

A Task-based Evaluation of French Morphological Resources and Tools

Morphology is a key component for many Language Technology applications. However, morphological relations, especially those relying on the derivation and compounding processes, are often addressed in a superficial manner. In this article, we focus on assessing the relevance of deep and motivated morphological knowledge in Natural Language Processing applications. We first describe an annotation experiment whose goal is to evaluate the role of morphology for one task, namely Question Answering (QA). We then highlight the kind of linguistic knowledge that is necessary for this particular task and propose a qualitative analysis of morphological phenomena in order to identify the morphological processes that are most relevant. Based on this study, we perform an intrinsic evaluation of existing tools and resources for French morphology, in order to quantify their coverage. Our conclusions provide helpful insights for using and building appropriate morphological resources and tools that could have a significant impact on the application performance

Plagiarism detection for Indonesian texts

As plagiarism becomes an increasing concern for Indonesian universities and research centers, the need of using automatic plagiarism checker is becoming more real. However, researches on Plagiarism Detection Systems (PDS) in Indonesian documents have not been well developed, since most of them deal with detecting duplicate or near-duplicate documents, have not addressed the problem of retrieving source documents, or show tendency to measure document similarity globally. Therefore, systems resulted from these researches are incapable of referring to exact locations of ``similar passage'' pairs. Besides, there has been no public and standard corpora available to evaluate PDS in Indonesian texts. To address the weaknesses of former researches, this thesis develops a plagiarism detection system which executes various methods of plagiarism detection stages in a workflow system. In retrieval stage, a novel document feature coined as phraseword is introduced and executed along with word unigram and character n-grams to address the problem of retrieving source documents, whose contents are copied partially or obfuscated in a suspicious document. The detection stage, which exploits a two-step paragraph-based comparison, is aimed to address the problems of detecting and locating source-obfuscated passage pairs. The seeds for matching source-obfuscated passage pairs are based on locally-weighted significant terms to capture paraphrased and summarized passages. In addition to this system, an evaluation corpus was created through simulation by human writers, and by algorithmic random generation. Using this corpus, the performance evaluation of the proposed methods was performed in three scenarios. On the first scenario which evaluated source retrieval performance, some methods using phraseword and token features were able to achieve the optimum recall rate 1. On the second scenario which evaluated detection performance, our system was compared to Alvi's algorithm and evaluated in 4 levels of measures: character, passage, document, and cases. The experiment results showed that methods resulted from using token as seeds have higher scores than Alvi's algorithm in all 4 levels of measures both in artificial and simulated plagiarism cases. In case detection, our systems outperform Alvi's algorithm in recognizing copied, shaked, and paraphrased passages. However, Alvi's recognition rate on summarized passage is insignificantly higher than our system. The same tendency of experiment results were demonstrated on the third experiment scenario, only the precision rates of Alvi's algorithm in character and paragraph levels are higher than our system. The higher Plagdet scores produced by some methods in our system than Alvi's scores show that this study has fulfilled its objective in implementing a competitive state-of-the-art algorithm for detecting plagiarism in Indonesian texts. Being run at our test document corpus, Alvi's highest scores of recall, precision, Plagdet, and detection rate on no-plagiarism cases correspond to its scores when it was tested on PAN'14 corpus. Thus, this study has contributed in creating a standard evaluation corpus for assessing PDS for Indonesian documents. Besides, this study contributes in a source retrieval algorithm which introduces phrasewords as document features, and a paragraph-based text alignment algorithm which relies on two different strategies. One of them is to apply local-word weighting used in text summarization field to select seeds for both discriminating paragraph pair candidates and matching process. The proposed detection algorithm results in almost no multiple detection. This contributes to the strength of this algorithm