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5,051
Morphologically-Rich Languages
"... This first joint meeting on Statistical Parsing of Morphologically Rich Languages and Syntactic Analysis of Non-Canonical English (SPMRL-SANCL) featured a shared task on statistical parsing of morpholog-ically rich languages (SPMRL). The goal of the shared task is to allow to train and test differen ..."
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This first joint meeting on Statistical Parsing of Morphologically Rich Languages and Syntactic Analysis of Non-Canonical English (SPMRL-SANCL) featured a shared task on statistical parsing of morpholog-ically rich languages (SPMRL). The goal of the shared task is to allow to train and test
Statistical Stemming of Morphologically Rich Languages
, 2010
"... We analyze current machine translation into Russian, a morphologically rich language, and present a technique for unsupervised statistical stemming. An initial pass is based on intuitions, and uses a CUDA kernel. As a later pass, we run EM. Since our model is relatively simple, the EM probabilities ..."
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We analyze current machine translation into Russian, a morphologically rich language, and present a technique for unsupervised statistical stemming. An initial pass is based on intuitions, and uses a CUDA kernel. As a later pass, we run EM. Since our model is relatively simple, the EM probabilities
Concurrent Constraint Programming
, 1993
"... This paper presents a new and very rich class of (con-current) programming languages, based on the notion of comput.ing with parhal information, and the con-commitant notions of consistency and entailment. ’ In this framework, computation emerges from the inter-action of concurrently executing agent ..."
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Cited by 502 (16 self)
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This paper presents a new and very rich class of (con-current) programming languages, based on the notion of comput.ing with parhal information, and the con-commitant notions of consistency and entailment. ’ In this framework, computation emerges from the inter-action of concurrently executing
Understanding and Using Context
- Personal and Ubiquitous Computing
, 2001
"... Context is a poorly used source of information in our computing environments. As a result, we have an impoverished understanding of what context is and how it can be used. In this paper, we provide an operational definition of context and discuss the different ways that context can be used by contex ..."
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Cited by 865 (0 self)
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, which we believe will provide additional support to application designers. 1. Introduction Humans are quite successful at conveying ideas to each other and reacting appropriately. This is due to many factors: the richness of the language they share, the common understanding of how the world works
Translating into Morphologically Rich Languages with Synthetic Phrases
"... Translation into morphologically rich languages is an important but recalcitrant problem in MT. We present a simple and effective approach that deals with the problem in two phases. First, a discriminative model is learned to predict inflections of target words from rich source-side annotations. The ..."
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Cited by 12 (3 self)
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Translation into morphologically rich languages is an important but recalcitrant problem in MT. We present a simple and effective approach that deals with the problem in two phases. First, a discriminative model is learned to predict inflections of target words from rich source-side annotations
Statistical Thesaurus Construction for a Morphologically Rich Language
"... Corpus-based thesaurus construction for Morphologically Rich Languages (MRL) is a complex task, due to the morphological variability of MRL. In this paper we explore alternative term representations, complemented by clustering of morphological variants. We introduce a generic algorithmic scheme for ..."
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Corpus-based thesaurus construction for Morphologically Rich Languages (MRL) is a complex task, due to the morphological variability of MRL. In this paper we explore alternative term representations, complemented by clustering of morphological variants. We introduce a generic algorithmic scheme
Using Resource-Rich Languages to Improve Morphological Analysis of Under-Resourced Languages
"... The world-wide proliferation of digital communications has created the need for language and speech processing systems for under-resourced languages. Developing such systems is challenging if only small data sets are available, and the problem is exacerbated for languages with highly productive morp ..."
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morphology. However, many under-resourced languages are spoken in multi-lingual environments together with at least one resource-rich language and thus have numerous borrowings from resource-rich languages. Based on this insight, we argue that readily available resources from resource-rich languages can
Generation of Verbal Stems in Derivationally Rich Language
"... The paper presents a procedure for generating prefixed verbs in Croatian comprising combinations of one, two or three prefixes. The result of this generation process is a pool of derivationally valid prefixed verbs, although not necessarily occuring in corpora. The statistics of occurences of genera ..."
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of generated verbs in Croatian National Corpus has been calculated. Further usage of such language resource with generated potential verbs is also suggested, namely, enrichment of Croatian Morphological Lexicon, Croatian Wordnet and CROVALLEX.
Statistical parsing of morphologically rich languages (spmrl) what, how and whither
- In Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages
, 2010
"... The term Morphologically Rich Languages (MRLs) refers to languages in which significant information concerning syntactic units and relations is expressed at word-level. There is ample evidence that the application of readily available statistical parsing models to such languages is susceptible to se ..."
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Cited by 24 (9 self)
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The term Morphologically Rich Languages (MRLs) refers to languages in which significant information concerning syntactic units and relations is expressed at word-level. There is ample evidence that the application of readily available statistical parsing models to such languages is susceptible
Improving Named Entity Recognition for Morphologically Rich Languages using Word
"... Abstract—In this paper, we addressed the Named Entity Recognition (NER) problem for morphologically rich languages by employing a semi-supervised learning approach based on neural networks. We adopted a fast unsupervised method for learning continuous vector representations of words, and used these ..."
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Abstract—In this paper, we addressed the Named Entity Recognition (NER) problem for morphologically rich languages by employing a semi-supervised learning approach based on neural networks. We adopted a fast unsupervised method for learning continuous vector representations of words, and used
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