Articles

This paper presents a method to combine a set of unsupervised algorithms that can accurately disambiguate word senses in a large, completely untagged corpus. Al- though most of the techniques for word sense resolution have been presented as stand-alone, it is our belief that full-fledged lexical ambiguity resolution should com- …...

We compare four similarity-based esti- mation methods against back-off and maximum-likelihood estimation meth- ods on a pseudo-word sense disam- biguation task in which we controlled for both unigram and bigram fre- quency. The similarity-based meth- ods perform up to 40% better on this particular task. We also conclude that events …...

We propose a new method of classifying documents into categories. We define for each category a finite mixture model based on soft clustering of words. We treat the problem of classifying documents as that of conducting statistical hypothesis testing over finite mixture models, and employ the EM algorithm to efficiently …...

As the text databases available to users be- come larger and more heterogeneous, genre becomes increasingly important for com- putational linguistics as a complement to topical and structural principles of classifi- cation. We propose a theory of genres as bundles of facets, which correlate with var- ious surface cues, and …...

This paper discusses research on distin- guishing word meanings in the context of information retrieval systems. We conduc- ted experiments with three sources of evid- ence for making these distinctions: mor- phology, part-of-speech, and phrases. We have focused on the distinction between homonymy and polysemy (unrelated vs. re- lated meanings). …...

Valiant showed that Boolean matrix multiplication (BMM) can be used for CFG parsing. We prove a dual re- sult: CFG parsers running in time O([Gl[w[ 3-e) on a grammar G and a string w can be used to multiply m x m Boolean matrices in time O(m3-e/3). In the process …...

In this paper we first propose a new sta- tistical parsing model, which is a genera- tive model of lexicalised context-free gram- mar. We then extend the model to in- clude a probabilistic treatment of both sub- categorisation and wh-movement. Results on Wall Street Journal text show that the parser …...

We introduce a typed feature logic system providing both universal implicational principles as well as defi- nite clauses over feature terms. We show that such an architecture supports a modular encoding of linguistic theories and allows for a compact representation using underspecification. The system is fully implemented and has been …...

ed from the subjects" segmentations serve as a target for evaluating two sets of algorithms that use utterance features to perform segmentation. On the first algorithm set, we evaluate and compare the correlation of discourse segmentation with three types of linguistic cues (referential noun phrases, cue words, and pauses). We …...

In this paper we describe the application of Memory-Based Learning to the problem of Prepositional Phrase attachment disam- biguation. We compare Memory-Based Learning, which stores examples in mem- ory and generalizes by using intelligent sim- ilarity metrics, with a number of recently proposed statistical methods that are well suited to …...

In this paper we present first results from a comparative study. Its aim is to test the feasibility of different inductive learn- ing techniques to perform the automatic acquisition of linguistic knowledge within a natural language database interface. In our interface architecture the machine learn- ing module replaces an elaborate …...

In this paper, we study the use of so-called word trigger pairs to improve an existing language model, which is typically a tri- gram model in combination with a cache component. A word trigger pair is de- fined as a long-distance word pair. We present two methods to select the …...

This paper presents a new view of ExplanatiomBased Learning (EBL) of nat- ural language parsing. Rather than em- ploying EBL for specializing parsers by in- ferring new ones, this paper suggests em- ploying EBL for learning how to reduce ambiguity only partially.We exemplify this by presenting a new EBL method …...

We examine the Differential Grammar, a representation designed to discriminate which of a set of eonfusable alternatives is most likely in the context it occurs in. This approach is useful whereever uncertainty may exist about the identity of a token or sequence of tokens, including in speech recognition, optical character …...

Stochastic categorial grammars (SCGs) are introduced as a more appropriate formal- ism for statistical language learners to es- timate than stochastic context free gram- mars. As a vehicle for demonstrating SCG estimation, we show, in terms of crossing rates and in coverage, that when training material is limited, SCG estimation …...

Newly born infants are able to finely discriminate almost all human speech contrasts and their phonemic category boundaries are initially identical, even for phonemes outside their target language. A connectionist model is described which ac- counts for this ability. The approach taken has been to develop a model of innately …...

We describe an automatic process for learn- ing word units in Japanese. Since the Japanese orthography has no spaces de- limiting words, the first step in building a Japanese speech recognition system is to define the units that will be recognized. Our method applies a compound-finding algorithm, previously used to …...

The present article demostrates the im- plementation of a psycholinguistic model of second language learners' interlanguage in an Intelligent Computer Assisted Lan- guage Learning (ICALL) system for study- ing second language acquisition. We have focused our work on the common interlan- guage structures of students at the same language level. …...

This paper presents a new approach to automatic word categorization which im- proves both the efficiency of the algorithm and the quality of the formed clusters. The unigram and the bigram statistics of a cor- pus of about two million words are used with an efficient distance function to mea- …...

In this paper, we study the problem of "learning new compositions of words from given ones with a specific syntactic struc- ture, e.g., A-N or V-N structures. We first cluster words according to the given com- positions, then construct a cluster-based compositional frame for each word cluster, which contains both …...