• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1409-1425
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• 2021

In wide-ranging information society, fast and easy access to information in language of one's choice is indispensable, which may be provided by using various multilingual Natural Language Processing (NLP) applications. Natural language text contains references among different language elements, called anaphoric links. Resolving anaphoric links is a key problem in NLP. Anaphora resolution is an essential part of NLP applications. Anaphoric links need to be properly interpreted for clear understanding of natural languages. For this purpose, a mechanism is desirable for the identification and resolution of these naturally occurring anaphoric links. In this paper, a framework based on Hobbs syntactic approach and a system developed by Lappin & Leass is proposed for resolution of reflexive anaphoric links, present in Urdu text documents. Generally, anaphora resolution process takes three main steps: identification of the anaphor, location of the candidate antecedent(s) and selection of the appropriate antecedent. The proposed framework is based on exploring the syntactic structure of reflexive anaphors to find out various features for constructing heuristic rules to develop an algorithm for resolving these anaphoric references. System takes Urdu text containing reflexive anaphors as input, and outputs Urdu text with resolved reflexive anaphoric links. Despite having scarcity of Urdu resources, our results are encouraging. The proposed framework can be utilized in multilingual NLP (m-NLP) applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1692-1705
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• 2024

In this paper, we present a method that integrates a Grammar Transducer as an external language model to enhance the accuracy of the pre-trained Korean End-to-end (E2E) Automatic Speech Recognition (ASR) model. The E2E ASR model utilizes the Connectionist Temporal Classification (CTC) loss function to derive hypothesis sentences from input audio. However, this method reveals a limitation inherent in the CTC approach, as it fails to capture language information from transcript data directly. To overcome this limitation, we propose a fusion approach that combines a clause-level n-gram language model, transformed into a Weighted Finite-State Transducer (WFST), with the E2E ASR model. This approach enhances the model's accuracy and allows for domain adaptation using just additional text data, avoiding the need for further intensive training of the extensive pre-trained ASR model. This is particularly advantageous for Korean, characterized as a low-resource language, which confronts a significant challenge due to limited resources of speech data and available ASR models. Initially, we validate the efficacy of training the n-gram model at the clause-level by contrasting its inference accuracy with that of the E2E ASR model when merged with language models trained on smaller lexical units. We then demonstrate that our approach achieves enhanced domain adaptation accuracy compared to Shallow Fusion, a previously devised method for merging an external language model with an E2E ASR model without necessitating additional training.

• Journal of information and communication convergence engineering
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• v.14 no.2
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• pp.97-105
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• 2016

With the increasing demand for interoperability among existing learning resource systems in order to enable the sharing of learning resources, such resources need to be annotated with ontologies that use different metadata standards. These different ontologies must be reconciled through ontology mediation, so as to cope with information heterogeneity problems, such as semantic and structural conflicts. In this paper, we propose an ontology-mapping technique using Semantic Web Rule Language (SWRL) to generate semantic mapping rules that integrate learning resources from different systems and that cope with semantic and structural conflicts. Reasoning rules are defined to support a semantic search for heterogeneous learning resources, which are deduced by rule-based inference. Experimental results demonstrate that the proposed approach enables the integration of learning resources originating from multiple sources and helps users to search across heterogeneous learning resource systems.

• English Language & Literature Teaching
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• v.12 no.1
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• pp.77-101
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• 2006

The present study examines various pedagogical functions of conversational repair strategies employed by the teacher in the ESL classroom. As part of interactional resources, conversational repair is defined as the treatment of trouble occurring in interactive language use and is originally designed to deal with communication problems. Research on conversational repair has focused on ordinary conversation and organization of repair practices. Studies on more pedagogical functions of repair sequences initiated by the teacher are very few. The data were from five hours of ESL structure classes in an intensive English institute at a large U.S. university. They were closely transcribed and microanalyzed following the conversation-analytic methodology. The analysis found that ESL teachers' repair techniques not only resolve communication problems but they are also designed to serve several important instructional purposes of teaching the target language. They include creating opportunities of comprehensible input, inducing modified comprehensible output from students, guiding and controlling student output, and initiating corrections by initiating repair.

• ETRI Journal
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• v.39 no.4
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• pp.455-466
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• 2017

This study focuses on a method for sequential data augmentation in order to alleviate data sparseness problems. Specifically, we present corpus expansion techniques for enhancing the coverage of a language model. Recent recurrent neural network studies show that a seq2seq model can be applied for addressing language generation issues; it has the ability to generate new sentences from given input sentences. We present a method of corpus expansion using a sentence-chain based seq2seq model. For training the seq2seq model, sentence chains are used as triples. The first two sentences in a triple are used for the encoder of the seq2seq model, while the last sentence becomes a target sequence for the decoder. Using only internal resources, evaluation results show an improvement of approximately 7.6% relative perplexity over a baseline language model of Korean text. Additionally, from a comparison with a previous study, the sentence chain approach reduces the size of the training data by 38.4% while generating 1.4-times the number of n-grams with superior performance for English text.

• Journal of information and communication convergence engineering
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• v.15 no.3
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• pp.170-174
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• 2017

Nowadays, people share and discuss scientific papers on social media such as the Web 2.0, big data, online forums, blogs, Twitter, Facebook and scholar community, etc. In addition to a variety of metrics such as numbers of citation, download, recommendation, etc., paper review text is also one of the effective resources for the study of scientific impact. The social media tools improve the research process: recording a series online scholarly behaviors. This paper aims to research the huge amount of paper reviews which have generated in the social media platforms to explore the implicit information about research papers. We implemented and shown the result of text mining on review texts using R language. And we found that Zika virus was the research hotspot and association research methods were widely used in 2016. We also mined the news review about one paper and derived the public opinion.

• Language and Information
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• v.9 no.2
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• pp.23-48
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• 2005

This study aims to discuss the word sense distinction of Korean middle verbs for restructuring KorLexVerb 1.0. Despite the duality of its meaning and syntactic structure, the word senses of middle verb are not clearly distinguished in current dictionaries. The underspecification causes very often mismatches that a same Korean word sense is used for two different English verb senses. A close examination on the syntactic and semantic properties of middle verb shows us that the word sense distinction and the reconstruction of hierarchical structure are indispensable. Finally, by doing this fine grained word sense distinction, we propose an alternative way of classification and description of the verb polysemy for KorLexVerb 1.0 as well as for dictionary-like language resources.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.2
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• pp.150-161
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• 1999

This paper deals with the design and development of a real-time integrated communication architecture for heterarchical SFCS(Shop Floor Control System). In autonomous agent-based heterarchical SFCS, each functional unit of parts and resources is equipped with an intelligent controller (agent) that acts as the representative of the entity. The controllers communicate and negotiate with other controllers on a real-time basis through message passing and bidding protocol to achieve mutual agreements for task sharing. ICPL(Integrated Communication Protocol and Language) is proposed for this purpose. ICPL is a language and a protocol for supporting communication among intelligent controllers. Based on the speech act theory, this paper proposes a semantic description for ICPL that associates the description of the cognitive states of controllers with the use of language primitives (message_type). Semantics for the basic set of ICPL messages is described. Eventually, an ICPL-based communication architecture can provide the implementation of the distributed and heterarchical SFCS, and makes the intelligent controller transparent to the negotiation problem.

• The Transactions of the Korea Information Processing Society
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• v.4 no.11
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• pp.2903-2913
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• 1997

This paper describes the design and implementation of the ParaC language that supports parallel programming on the shared memory and distributed memory parallel machine. The ParaC language is designed for the effective use of system resources of scalable parallel systems. The goal is achieved by adding parallel and synchronization constructs for shared address spaces, and remote task constructs for distributed address spaces. This paper also shows the translation method, and we implement the translator and the run-time library for parallel execution of extended constructs.

• Language and Information
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• v.3 no.1
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• pp.65-82
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• 1999

The interests in Machine Translation(MT) have gotten revitalized lately with the rapid expansion of internet users. MT technology has gone through several different stages of development, but the longest surviving methods usually maintains the following characteristics: the expand ability and flexibility based on proved linguistic formalism, the transfer method of translation, the continued efforts of systematic updates being made into the system. This paper introduces one such system, L&H Korean-English bidirectional MT system. This system uses Lexical-Functional Grammar as its linguistic framework. It also adopts the transfer method of MT and has been around on the market for over 10 years for other language pairs. Currently, the system covers over 10 different languages including Chinese, Japanese and Arabic, in addition to European languages. This paper will review the system in its core and discuss related tools and resources be ing used to enhance the quality of translation.