Co-occurrence

Prematurity and respiratory distress syndrome (RDS) are strongly associated. RDS continues to be an important contributor to neonatal mortality in low- and middle-income countries. This study aimed to identify clusters of preterm live births and RDS-associated neonatal deaths, and their cooccurrence pattern in São Paulo State, Brazil, between 2004 and 2015.

10p viferrari 28-11-2022 9 2   Download

This work consists of six phases which are registration, authentication, face detection, features extraction, image similarity, and image retrieval. The current study runs on a database of 810 images which was borrowed from face94 to measure the performance of image retrieval.

22p spiritedaway36 28-11-2021 13 2   Download

Discovering the key microbial species and environmental factors of microbial community and characterizing their relationships with other members are critical to ecosystem studies. The microbial cooccurrence patterns across a variety of environmental settings have been extensively characterized.

12p visilicon2711 20-08-2021 10 1   Download

Recent investigations show a remarkable convergence among contemporary unification-based formalisms for syntactic description. This convergence is now i t s e l f becoming an object of study, and there is an increasing recognition of the need for e x p l i c i t characterizations of the properties that relate and distinguish similar grammar formalisms. The paper proposes a series of changes in the formalism of Generalized Phrase Structure Grammar that throw light on its relation to Functional Unification Grammar.

4p buncha_1 08-05-2013 37 1   Download

We describe a novel method that extracts paraphrases from a bitext, for both the source and target languages. In order to reduce the search space, we decompose the phrase-table into sub-phrase-tables and construct separate clusters for source and target phrases. We convert the clusters into graphs, add smoothing/syntacticinformation-carrier vertices, and compute the similarity between phrases with a random walk-based measure, the commute time.

10p bunthai_1 06-05-2013 43 3   Download

The degree of dominance of a sense of a word is the proportion of occurrences of that sense in text. We propose four new methods to accurately determine word sense dominance using raw text and a published thesaurus. Unlike the McCarthy et al. (2004) system, these methods can be used on relatively small target texts, without the need for a similarly-sensedistributed auxiliary text. We perform an extensive evaluation using artificially generated thesaurus-sense-tagged data.

8p bunthai_1 06-05-2013 48 2   Download

We explore learning prepositionalphrase attachment in Dutch, to use it as a filter in prosodic phrasing. From a syntactic treebank of spoken Dutch we extract instances of the attachment of prepositional phrases to either a governing verb or noun. Using cross-validated parameter and feature selection, we train two learning algorithms, TB I and RIPPER, 011 making this distinction, based on unigram and bigram lexical features and a cooccurrence feature derived from WWW counts.

8p bunthai_1 06-05-2013 51 1   Download

This paper addresses the problem of developing a large semantic lexicon for natural language processing. The increas~g availability of machine readable documents offers an opportunity to the field of lexieal semantics, by providing experimental evidence of word uses (on-line texts) and word definitions (on-line dictionaries). The system presented hereafter, PETRARCA, detects word e.occurrences from a large sample of press agency releases on finance and economics, and uses these associations to build a ease-based semantic lexicon. ...

8p bungio_1 03-05-2013 33 1   Download

C o m m o n algorithms for sentence and word-alignment allow the automatic identification of word translations from paxalhl texts. This study suggests that the identification of word translations should also be possible with non-paxMlel and even unrelated texts. The m e t h o d proposed is based on the assumption t h a t there is a correlation between the patterns of word cooccurrences in texts of different languages.

3p bunmoc_1 20-04-2013 40 2   Download

In m a n y applications of natural language processing it is necessary to determine the likelihood of a given word combination. For example, a speech recognizer m a y need to determine which of the two word combinations "eat a peach" and "eat a beach" is more likely. Statistical NLP methods determine the likelihood of a word combination according to its frequency in a training corpus. However, the nature of language is such that m a n y word combinations are infrequent and do not occur in a given corpus. ...

7p bunmoc_1 20-04-2013 37 1   Download

In recent years there is much interest in word cooccurrence relations, such as n-grams, verbobject combinations, or cooccurrence within a limited context. This paper discusses how to estimate the probability of cooccurrences that do not occur in the training data. We present a method that makes local analogies between each specific unobserved cooccurrence and other cooccurrences that contain similar words, as determined by an appropriate word similarity metric.

8p bunmoc_1 20-04-2013 39 3   Download

This paper presents a corpus-based approach for deriving heuristics to locate the antecedents of relative pronouns. The technique dupficates the performance of hand-coded rules and requires human intervention only during the training phase. Because the training instances are built on parser output rather than word cooccurrences, the technique requires a small number of training examples and can be used on small to medium-sized corpora.

8p bunmoc_1 20-04-2013 43 1   Download

We describe a method for obtaining subject-dependent word sets relative to some (subjecO domain. Using the subject classifications given in the machine-readable version of Longman's Dictionary of Contemporary English, we established subject-dependent cooccurrence links between words of the defining vocabulary to construct these "neighborhoods". Here, we describe the application of these neighborhoods to information retrieval, and present a method of word sense disambiguation based on these co-occurrences, an extension of previous work. ...

7p bunmoc_1 20-04-2013 53 2   Download

We describe an approach to improve the bilingual cooccurrence dictionary that is used for word alignment, and evaluate the improved dictionary using a version of the Competitive Linking algorithm. We demonstrate a problem faced by the Competitive Linking algorithm and present an approach to ameliorate it. In particular, we rebuild the bilingual dictionary by clustering similar words in a language and assigning them a higher cooccurrence score with a given word in the other language than each single word would have otherwise.

8p bunmoc_1 20-04-2013 46 2   Download

We study distributional similarity measures for the purpose of improving probability estimation for unseen cooccurrences. Our contributions are three-fold: an empirical comparison of a broad range of measures; a classification of similarity functions based on the information that they incorporate; and the introduction of a novel function that is superior at evaluating potential proxy distributions.

8p bunrieu_1 18-04-2013 43 3   Download

This paper presents a method of improving the accuracy of subcategorization frames (SCFs) acquired from corpora to augment existing lexicon resources. I estimate a confidence value of each SCF using corpus-based statistics, and then perform clustering of SCF confidencevalue vectors for words to capture cooccurrence tendency among SCFs in the lexicon.

6p bunbo_1 17-04-2013 57 2   Download

In this paper, we present an unsupervised methodology for propagating lexical cooccurrence vectors into an ontology such as WordNet. We evaluate the framework on the task of automatically attaching new concepts into the ontology. Experimental results show 73.9% attachment accuracy in the first position and 81.3% accuracy in the top-5 positions. This framework could potentially serve as a foundation for ontologizing lexical-semantic resources and assist the development of other largescale and internally consistent collections of semantic information. ...

8p bunbo_1 17-04-2013 45 2   Download

Identification of transliterated names is a particularly difficult task of Named Entity Recognition (NER), especially in the Chinese context. Of all possible variations of transliterated named entities, the difference between PRC and Taiwan is the most prevalent and most challenging. In this paper, we introduce a novel approach to the automatic extraction of diverging transliterations of foreign named entities by bootstrapping cooccurrence statistics from tagged and segmented Chinese corpus. Preliminary experiment yields promising results and shows its potential in NLP applications. ...

4p hongvang_1 16-04-2013 51 3   Download

Situation entities (SEs) are the events, states, generic statements, and embedded facts and propositions introduced to a discourse by clauses of text. We report on the first datadriven models for labeling clauses according to the type of SE they introduce. SE classification is important for discourse mode identification and for tracking the temporal progression of a discourse.

8p hongvang_1 16-04-2013 58 2   Download

This paper examines what kind of similarity between words can be represented by what kind of word vectors in the vector space model. Through two experiments, three methods for constructing word vectors, i.e., LSA-based, cooccurrence-based and dictionary-based methods, were compared in terms of the ability to represent two kinds of similarity, i.e., taxonomic similarity and associative similarity.

8p hongvang_1 16-04-2013 48 2   Download