• Journal of the Korean Institute of Telematics and Electronics
• /
• v.26 no.12
• /
• pp.1975-1983
• /
• 1989

Implementing the linguistic theories on computer, we resolve the problems for restrictions of computer and increase processing efficiency for systemization not for linguistic theory itself. Thus, we modify the grammatical theory to be applied to systems. This paper reports the various problems about constructing dictionaies, defining rules, and appling universal principles and metarules, which is caused to implement the systems based on GPSG. In semantic interpretations, logical expressions which correspond Montague grammar are acquired, and we make a rule connect with several logical expressions. And we show the efficiency of the this method through implementing parser.

• Journal of KIISE:Software and Applications
• /
• v.37 no.3
• /
• pp.205-213
• /
• 2010

We introduce a natural language sentence generation (NLG) method based on learning of word-association patterns. Existing NLG methods assume the inherent grammar rules or use template based method. Contrary to the existing NLG methods, the presented method learns the words-association patterns using only the co-occurrence of words without additional information such as tagging. We employ the hypernetwork method to analyze and represent the words-association patterns. As training going on, the model complexity is increased. After completing each training phase, natural language sentences are generated using the learned hyperedges. The number of grammatically plausible sentences increases after each training phase. We confirm that the proposed method has a potential for learning grammatical properties of training corpuses by comparing the diversity of grammatical rules of training corpuses and the generated sentences.

• International Journal of Contents
• /
• v.1 no.2
• /
• pp.39-43
• /
• 2005

In this paper, we describe a generation mechanism of semantic-based queries for high accuracy information retrieval and question answering. It is difficult to offer the correct retrieval result because general information retrieval systems do not analyze the semantic of user's natural language question. We analyze user's question semantically and extract semantic features, and we .generate semantic-based queries using them. These queries are generated using the se-mantic-based question analysis grammar and the query generation rule. They are represented as semantic features and grammatical morphemes that consider semantic and syntactic structure of user's questions. We evaluated our mechanism using 100 questions whose answer type is a person in the TREC-9 corpus and Web. There was a 0.28 improvement in the precision at 10 documents when semantic-based queries were used for information retrieval.

• MALSORI
• /
• no.38
• /
• pp.1-24
• /
• 1999

There is an indisputable connection between prosody and focus. The focal prominence in Korean, a prosodic realization of pitch prominence in an utterance, defines a focused constituent, the domain of which is identified by the Focus Identification Principle. To this is added the Basic Focus Rule which makes it possible to capture and interpret the focal domain, which can then be tested against the available context. The focal domain can be contextually made available by setting it off with information structure boundaries(I/S) identified by the Information Structure Identification Principle. The fragment of the utterance enclosed within the IS boundaries can be recognized as 'new' information with the help of the Focus Domain Identification Rule. Since information structures are pragmatically tied to semantic levels of grammatical systems, the Basic Focus Rule is now replaced by the Focal Prominence Principle ensuring the focal prominence within the focal domain. Close relationships exist between patterns of intonation and their expressiveness in terms of giving a pragmatically-oriented description of focus. This is particularly manifested in Korean sentences containing contrastiveness.

• Language and Information
• /
• v.19 no.1
• /
• pp.19-36
• /
• 2015

Honorific agreement is one of the main properties in languages like Korean, playing a pivotal role in appropriate communication. This makes the deep processing of honorific information crucial in various computational applications such as spoken language translation and generation. This paper shows that departing from previous literature, an adequate analysis of Korean honorification needs to involve a system that has access not only to morpho-syntax but to semantics and pragmatics as well. Along these lines, this paper offers a constraint-based HPSG analysis of Korean honorification in which the enriched lexical information tightly interacts with syntactic, semantic, and pragmatic levels for the proper honorific system.

• Proceedings of the KSPS conference
• /
• 2007.05a
• /
• pp.135-137
• /
• 2007

This study has experimented and materialized a computational lexical processing model which hybridizes full model and decomposition model as applying lexical acquisition, one of early stages of human lexical processes, to Korean. As the result of the study, we could simulate the lexical acquisition process of linguistic input through experiments and studying, and suggest a theoretical foundation for the order of acquitting certain grammatical categories. Also, the model of this study has shown proofs with which we can infer the type of the mental lexicon of the human cerebrum through fu1l-list dictionary and decomposition dictionary which were automatically produced in the study.

• Language and Information
• /
• v.14 no.1
• /
• pp.1-24
• /
• 2010

The complexity of comparative constructions in each language has given challenges to both theoretical and computational analyses. This paper first identifies types of comparative constructions in Korean and discusses their main grammatical properties. It then builds a syntactic parser couched upon the typed feature structure grammar, HPSG and proposes a context-dependent interpretation for the comparison. To check the feasibility of the proposed analysis, we have implemented the grammar into the existing Korean Resource Grammar. The results show us that the grammar we have developed here is feasible enough to parse Korean comparative sentences and yield proper semantic representations though further development is needed for a finer model for contextual information.

• Journal of Multimedia Information System
• /
• v.5 no.3
• /
• pp.147-154
• /
• 2018

Natural language processing (NLP) is an emerging research area in which we study how machines can be used to perceive and alter the text written in natural languages. We can perform different tasks on natural languages by analyzing them through various annotational tasks like parsing, chunking, part-of-speech tagging and lexical analysis etc. These annotational tasks depend on morphological structure of a particular natural language. The focus of this work is part-of-speech tagging (POS tagging) on Hindi language. Part-of-speech tagging also known as grammatical tagging is a process of assigning different grammatical categories to each word of a given text. These grammatical categories can be noun, verb, time, date, number etc. Hindi is the most widely used and official language of India. It is also among the top five most spoken languages of the world. For English and other languages, a diverse range of POS taggers are available, but these POS taggers can not be applied on the Hindi language as Hindi is one of the most morphologically rich language. Furthermore there is a significant difference between the morphological structures of these languages. Thus in this work, a POS tagger system is presented for the Hindi language. For Hindi POS tagging a hybrid approach is presented in this paper which combines "Probability-based and Rule-based" approaches. For known word tagging a Unigram model of probability class is used, whereas for tagging unknown words various lexical and contextual features are used. Various finite state machine automata are constructed for demonstrating different rules and then regular expressions are used to implement these rules. A tagset is also prepared for this task, which contains 29 standard part-of-speech tags. The tagset also includes two unique tags, i.e., date tag and time tag. These date and time tags support all possible formats. Regular expressions are used to implement all pattern based tags like time, date, number and special symbols. The aim of the presented approach is to increase the correctness of an automatic Hindi POS tagging while bounding the requirement of a large human-made corpus. This hybrid approach uses a probability-based model to increase automatic tagging and a rule-based model to bound the requirement of an already trained corpus. This approach is based on very small labeled training set (around 9,000 words) and yields 96.54% of best precision and 95.08% of average precision. The approach also yields best accuracy of 91.39% and an average accuracy of 88.15%.

• Journal of Korea Multimedia Society
• /
• v.23 no.9
• /
• pp.1191-1200
• /
• 2020

In this paper, we proposed DEVS based programming education model that based on the cognitive information processing theory, not a grammatical programming education, and studied effectiveness analysis using computer thinking patterns. By creating a small range of patterns in the grammar which underlies the programming language and solving various examples through combinations, this paper shows an education method to develop problem-solving skills based on algorithmic thinking. The purpose of this study is to facilitate non-majors learn programming languages and understand patterned program structures when writing programs by patterning of control statements which the most important in learning programming.

• Language and Information
• /
• v.7 no.1
• /
• pp.55-68
• /
• 2003

Most of the previous approaches to English agreement phenomena have relied upon only one component of the grammar (e.g., either syntax, or semantics, or pragmatics). This paper argues that interrelationships among different grammatical components play crucial roles in such phenomenon too (cf. Kathol 1999 and Hudson 1999). The paper proposes that, contrary to traditional wisdom, English determiner-noun agreement is morpho-syntactic whereas subject-verb and pronoun-antecedent agreement are reflections of index agreement (cf. Pollard and Sag 1994). The present hybrid analysis of English agreement shows the importance of the interaction of different components of the grammar in accounting for English agreement phenomena. In particular, once we allow morphology to tightly interact with the system of syntax, semantics, or even pragmatics, we could provide a solution to some puzzling English agreement phenomena. This allows a more principled theory of English agreement.