Articles

AbstractText condensation aims at shortening the length of an utterance without losing essential textual information. In this paper, we report on the implementation and preliminary evaluation of a sentence condensation tool for Greek using a manually constructed table of 450 lexical paraphrases, and a set of rules that delete syntactic …...

AbstractHardly any other kind of text structures is as notoriously difficult to read as patents. This is first of all due to their abstract vocabulary and their very complex syntactic constructions. Especially the claims in a patent are a challenge: in accordance with international patent writing regulations, each claim must …...

AbstractThe growing dependence of modern society on the Web as a vital source of information and communication has become inevitable. However, the Web has become an ideal channel for various terrorist organisations to publish their misleading information and send unintelligible messages to communicate with their clients as well. The increase …...

AbstractThis paper describes a syllabification based conversion method for converting romanized Persian text to the traditional Arabic-based writing system. The system is implemented in Xerox XFST and relies on rule based conversion of words rather than using morphological analysis. The paper presents a brief evaluation of the accuracy of the …...

AbstractIn this paper we present and discuss the results of a text coherence experiment performed on a small corpus of Romanian text from a number of alternative high school manuals. During the last 10 years, an abundance of alternative manuals for high school was produced and distributed in Romania. Due …...

AbstractIn this paper, we describe an approach that aims to model heterogeneous resources for information extraction. Document is modeled in graph representation that enables better understanding of multi-media document and its structure which ultimately could result better cross-media information extraction. We also describe our proposed algorithm that segment document-based on …...

AbstractIn this paper Semantic Press, a tool for the automatic press review, is introduced. It is based on Text Mining technologies and is tailored to meet the needs of the eGovernment and eParticipation communities. First, a general description of the application demands emerging from the eParticipation and eGovernment sectors is …...

AbstractWe present a topic boundary detection method that searches for connections between sequences of utterances in multi party dialogues. The connections are established based on word identity. We compare our method to a state-of-the art automatic Topic boundary detection method that was also used on multi party dialogues. We checked …...

AbstractThis paper proposes an extension of Sumida and Torisawa’s method of acquiring hyponymy relations from hierachical layouts in Wikipedia (Sumida and Torisawa, 2008). We extract hyponymy relation candidates (HRCs) from the hierachical layouts in Wikipedia by regarding all subordinate items of an item x in the hierachical layouts as x’s …...

AbstractThis paper presents various strategies for improving the extraction performance of less prominent relations with the help of the rules learned for similar relations, for which large volumes of data are available that exhibit suitable data properties. The rules are learned via a minimally supervised machine learning system for relation …...

AbstractEach year NIST releases a set of question, document id, answer-triples for the factoid questions used in the TREC Question Answering track. While this resource is widely used and proved itself useful for many purposes, it also is too coarse a grain-size for a lot of other purposes. In this …...

AbstractWe aim to characterize the comparability of corpora, we address this issue in the trilingual context through the distinction of expert and non expert documents. We work separately with corpora composed of documents from the medical domain in three languages (French, Japanese and Russian) which present an important linguistic distance …...

AbstractThe release of the Enron corpus provided a unique resource for studying aspects of email use, because it is largely unfiltered, and therefore presents a relatively complete collection of emails for a reasonably large number of correspondents. This paper describes a newly created subcorpus of the Enron emails which we …...

AbstractRelation extraction is the task of finding pre-defined semantic relations between two entities or entity mentions from text. Many methods, such as feature-based and kernel-based methods, have been proposed in the literature. Among them, feature-based methods draw much attention from researchers. However, to the best of our knowledge, existing feature-based …...

AbstractWe report about a project which brings together Natural Language Processing and eLearning. One of the functionalities developed within this project is the possibility to annotate learning objects semi-automatically with keywords. To this end, a keyword extractor has been created which is able to handle documents in 8 languages. The …...

AbstractWe have analyzed the SPEX algorithm by Bernstein and Zobel (2004) for detecting co-derivative documents using duplicate n-grams. Although we totally agree with the claim that not using unique n-grams can greatly increase the efficiency and scalability of the process of detecting co-derivative documents, we have found serious bottlenecks in …...

AbstractMany systems have been developed in the past few years to assist researchers in the discovery of knowledge published as English text, for example in the PubMed database. At the same time, higher level collective knowledge is often published using a graphical notation representing all the entities in a pathway …...

AbstractWhat kinds of lexical resources are helpful for extracting useful information from domain-specific documents? Although domain-specific documents contain much useful knowledge, it is not obvious how to extract such knowledge efficiently from the documents. We need to develop techniques for extracting hidden information from such domain-specific documents. These techniques do …...

AbstractIn this paper we present an algorithm for automatic extraction of textual elements, namely titles and full text, associated with news stories in news web pages. We propose a supervised machine learning classification technique based on the use of a Support Vector Machine (SVM) classifier to extract the desired textual …...

AbstractWe address here the need to assist users in rapidly accessing the most important or strategic information in the text corpus by identifying sentences carrying specific information. More precisely, we want to identify contribution of authors of scientific papers through a categorization of sentences using rhetorical and lexical cues. We …...