Articles

This paper discusses the supervised learn- ing of morphology using stochastic trans- ducers, trained using the Expectation- Maximization (EM) algorithm. Two ap- proaches are presented: first, using the transducers directly to model the process, and secondly using them to define a sim- ilarity measure, related to the Fisher ker- nel …...

We explore how active learning with Sup- port Vector Machines works well for a non-trivial task in natural language pro- cessing. We use Japanese word segmenta- tion as a test case. In particular, we discuss how the size of a pool affects the learning curve. It is found that in …...

This paper presents a revision learn- ing method that achieves high per- formance with small computational cost by combining a model with high generalization capacity and a model with small computational cost. This method uses a high capacity model to revise the output of a small cost model. We apply …...

This paper describes algorithms which rerank the top N hypotheses from a maximum-entropy tagger, the applica- tion being the recovery of named-entity boundaries in a corpus of web data. The first approach uses a boosting algorithm for ranking problems. The second ap- proach uses the voted perceptron algo- rithm. Both …...

This paper describes how a machine- learning named entity recognizer (NER) on upper case text can be improved by us- ing a mixed case NER and some unlabeled text. The mixed case NER can be used to tag some unlabeled mixed case text, which are then used as additional training …...

This paper proposes a Hidden Markov Model (HMM) and an HMM-based chunk tagger, from which a named entity (NE) recognition (NER) system is built to recognize and classify names, times and numerical quantities. Through the HMM, our system is able to apply and integrate four types of internal and external …...

The paper proposes and empirically moti- vates an integration of supervised learning with unsupervised learning to deal with human biases in summarization. In par- ticular, we explore the use of probabilistic decision tree within the clustering frame- work to account for the variation as well as regularity in human created …...

NeATS is a multi-document summarization system that attempts to extract relevant or interesting portions from a set of documents about some topic and present them in coherent order. NeATS is among the best performers in the large scale summarization evaluation DUC 2001. 1...

We present a document compression sys- tem that uses a hierarchical noisy-channel model of text production. Our compres- sion system first automatically derives the syntactic structure of each sentence and the overall discourse structure of the text given as input. The system then uses a sta- tistical hierarchical model of …...

Answer Validation is an emerging topic in Question Answering, where open do- main systems are often required to rank huge amounts of candidate answers. We present a novel approach to answer valida- tion based on the intuition that the amount of implicit knowledge which connects an answer to a question …...

We present an architecture for the integra- tion of shallow and deep NLP components which is aimed at flexible combination of different language technologies for a range of practical current and future appli- cations. In particular, we describe the inte- gration of a high-level HPSG parsing sys- tem with different …...

We describe a case study in which a memory-based learning algorithm is trained to simultaneously chunk sentences and assign grammatical function tags to these chunks. We compare the algo- rithm’s performance on this parsing task with varying training set sizes (yielding learning curves) and different input repre- sentations. In particular …...

We discuss a framework for teaching con- trastive translation-oriented linguistics to students of machine translation. The frame- work embodies a classification of cross- linguistic differences and a demonstration of how the neutralization of such differences in abstract representations can make trans- fer modules simpler. We illustrate by means of examples …...

Word sense is ambiguous in natural language processing (NLP). This phenomenon is particularly keen in cases involving noun-verb (NV) word-pairs. This paper describes a sense-based noun-verb event frame (NVEF) identifier that can be used to disambiguate word sense in Chinese sentences effectively. A knowledge representation system (the NVEF-KR tree) for …...

Information Extraction (IE), defined as the activity to extract structured knowl- edge from unstructured text sources, of- fers new opportunities for the exploitation of biological information contained in the vast amounts of scientific literature. But while IE technology has received increas- ing attention in the area of molecular bi- ology, …...

We describe the use of clinical data present in the medical record to determine the relevance of research evidence from literature databases. We studied the effect of using automated knowledge approaches as compared to physician’s selection of articles, when using a traditional information retrieval system. Three methods were evaluated. The …...

� Objectives:� To� automatically� extend� downwards�an�existing�biomedical�termi- nology� using� a� corpus� and� both� lexical� and�terminological�knowledge.�Methods:� Adjectival� modifiers� are� removed� from� terms� extracted� from� the� corpus� (three� million� noun� phrases� extracted� from� MEDLINE),� and� demodified� terms� are� searched� for� in� the� terminology� (UMLS� Metathesaurus,�restricted�to�disorders�and� procedures).� A� phrase� from� MEDLINE� becomes�a�candidate�term�in�the�Metathe- saurus�if�the�following�two�requirements� are� …...

Document retrieval in languages with a rich and complex morphology – par- ticularly in terms of derivation and (single-word) composition – suffers from serious performance degradation with the stemming-only query-term-to-text-word matching paradigm. We propose an alternative approach in which morpholog- ically complex word forms are segmented into relevant subwords (such …...

We describe our use of an existing re- source, the Mouse Anatomical Nomen- clature, to improve a symbolic interface to anatomically-indexed gene expression data. The goal is to reduce user effort in specifying anatomical structures of inter- est and increase precision and recall. 1...

NLP systems will be more portable among medical domains if acquisition of semantic lexicons can be facilitated. We are pursuing lexical acquisition through the syntactic relationships of words in medical corpora. Therefore we require a syntactic parser which is flexible, portable, captures head-modifier pairs and does not require a large …...