Articles

We� present� a� hybrid� text� mining method� for� finding� abbreviations� and their�definitions�in�free�format�texts.�To deal� with� the� problem,� this� method employs� pattern-based� abbreviation rules�in�addition�to�text�markers�and�cue words.�The�pattern-based�rules�describe how� abbreviations� are� formed� from definitions.� Rules� can� be� generated automatically� and/or� manually� and� can be� augmented� when� the� system processes� new� documents.� The proposed�method�has�the�advantages�of high� accuracy,� …...

Many classification problems require decisions among a large number of competing classes. These tasks, however, are not handled well by general pur- pose learning methods and are usually addressed in an ad-hoc fashion. We suggest a general approach – a sequential learning model that utilizes classi- fiers to sequentially restrict …...

We evaluate empirically a scheme for combining classifiers, known as stacked generalization, in the context of anti-spam filtering, a novel cost-sensitive application of text categorization. Unsolicited commercial e- mail, or “spam”, floods mailboxes, causing frustration, wasting bandwidth, and exposing minors to unsuitable content. Using a public corpus, we show that …...

Computational learning of natural lan- guage is often attempted without using the knowledge available from other re- search areas such as psychology and linguistics. This can lead to systems that solve problems that are neither theoretically or practically useful. In this paper we present a system CLL which aims to …...

This paper shows that linguistic tech- niques along with machine learning can extract high quality noun phrases for the purpose of providing the gist or summary of email messages. We describe a set of comparative experi- ments using several machine learning algorithms for the task of salient noun phrase extraction. …...

Information about the animacy of nouns is important for a wide range of tasks in NLP. In this paper, we present a method for determining the animacy of English nouns using WordNet and machine learning techniques. Our method firstly categorises the senses from WordNet using an annotated corpus and then …...

An algorithm is presented for learning a phrase-structure grammar from tagged text. It clusters sequences of tags to- gether based on local distributional in- formation, and selects clusters that sat- isfy a novel mutual information crite- rion. This criterion is shown to be re- lated to the entropy of a …...

This paper reports on the LEARNING COMPUTATIONAL GRAMMARS (LCG) project, a postdoc network devoted to studying the application of machine learning techniques to grammars suit- able for computational use. We were in- terested in a more systematic survey to understand the relevance of many fac- tors to the success of …...

We present a general model for PP attach- ment resolution and NP analysis in French. We make explicit the different assumptions our model relies on, and show how it gener- alizes previously proposed models. We then present a series of experiments conducted on a corpus of newspaper articles, and as- …...

Significant amount of work has been devoted recently to develop learning techniques that can be used to gener- ate partial (shallow) analysis of natu- ral language sentences rather than a full parse. In this work we set out to evalu- ate whether this direction is worthwhile by comparing a learned …...

This paper describes a Natural Lan- guage Learning method that extracts knowledge in the form of semantic pat- terns with ontology elements associated to syntactic components in the text. The method combines the use of EuroWord- Net’s ontological concepts and the cor- rect sense of each word assigned by a …...

Selectional preference learning methods have usually focused on word- to-class relations, e.g., a verb selects as its subject a given nominal class. This papers extends previous statistical models to class-to-class preferences, and presents a model that learns selectional preferences for classes of verbs. The motivation is twofold: different senses of …...

Memory-based learning (MBL) has enjoyed considerable success corpus-based natural language process-in ing (NLP) tasks and is thus a reliable method of getting a high-level of per- formance when building corpus-based NLP systems. However there is a bottleneck in MBL whereby any novel testing item has to be compared against all …...

One of the particular characteristics of text classification tasks is that they present large class imbalances. Such a problem can easily be tackled using re- sampling methods. However, although these approaches are very simple to im- plement, tuning them most effectively is not an easy task. In particular, it is …...

In a text-to-speech (TTS) conversion system based on the time-domain pitch-synchronous overlap-add (TD-PSOLA) method, accurate estimation of pitch periods and pitch marks is necessary for pitch modification to assure an optimal quality of the synthetic speech. In general, there are two major issues on pitch marking: pitch detection and location …...

A phonetic representation of a language is used to describe the corresponding pronunciation and synthesize the acoustic model of any vocabulary. In order to obtain better phonetic representation, context-dependent units are used to model co-articulation effects between phones and have been broadly in speech recognition. However, this representation generally increases …...

The design and compilation of the CUCall telephone speech corpora is described in this paper. Speech database is an indispensable resource for research and development of state-of-the-art spoken language technology. These speech recognition systems rely greatly on a huge amount of well-designed and appropriately processed speech data for parameters training. …...

In this paper, we describe the creation of Chinese zero anaphora resolution rules by performing experiments. The rules were constructed based on the centering model. In the experiments, we selected several texts as testing examples. We compared the referents of zero anaphors in the testing texts identified by hand with …...

Research into the automatic acquisition of subcategorization frames from corpora is starting to produce large-scale computational lexicons which include valuable frequency in- formation. However, the accuracy of the resulting lexicons shows room for improve- ment. One source of error lies in the lack of accurate back-off estimates for subcatego- rization …...

This paper revisits the one sense per collocation hypothesis using fine-grained sense distinctions and two different corpora. We show that the hypothesis is weaker for fine-grained sense distinctions (70% vs. 99% reported earlier on 2-way ambiguities). We also show that one sense per collocation does hold across corpora, but that …...