• ETRI Journal
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• v.28 no.6
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• pp.803-806
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• 2006

This letter addresses a structural disambiguation method for Korean adverbs based on the correlative relation constraints between adverbs and modifiees, and the morphological context information of sentences. Using the proposed method, we improved the dependency parsing accuracy of adverbs from 79.2 to 89%. The experimental result shows that the proposed method is especially expert in parsing adverbs which can modify multiple word classes or have a long distance dependency relation to their modifiees.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.482-485
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• 2000

A modified watershed transform is proposed which is context-free marker-controlled and minima imposition-free to reduce the over-segmentation and to speedup the transform. In contrast to the conventional methods in which a priori knowledge, such as flat zones, zones of homogeneous texture, and morphological distance, is required for marker extraction, context-free marker extraction is proposed by using the attention operator based on the GST (generalized symmetry transform). By using the context-free marker, the proposed watershed transform exploit marker-constrained labeling to speedup the computation and to reduce the over-segmentation by eliminating the unnecessary geodesic reconstruction such as the minima imposition and thereby eliminating the necessity of the post-processing of region merging. The simulation results show that the proposed method can extract context-free markers inside the objects from the complex background that includes multiple objects and efficiently reduces over-segmentation and computation time.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.375-381
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• 2022

The main objective of an Information Retrieval System (IRS) is to obtain suitable information within a reasonable time to satisfy a user need. To achieve this purpose, an IRS should have a good indexing system that is based on natural language processing.In this context, we focus on the available Arabic language processing techniques for an IRS with the goal of contributing to an improvement in the performance. Our contribution consists of integrating morphological analysis into an IRS in order to compare the impact of morphological analysis with that of stemming algorithms.

• Phonetics and Speech Sciences
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• v.4 no.3
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• pp.129-136
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• 2012

Korean alveolar fricatives are late-developing speech sounds. Most previous research on phonemes used individual words or pseudo words to produce sounds, but word-level phonological analysis does not always reflect a child's practical articulation ability. Also, there has been limited research on articulation development looking at speech production by grammatical morphemes despite its importance in Korean language. Therefore, this research examines the articulation development and phonological patterns of the /s/ phoneme in terms of morphological types produced in children's spontaneous conversational speech. The subjects were twenty-two typically developing 3- and 4-year-old Koreans. All children showed normal levels in three screening tests: hearing, vocabulary, and articulation. Spontaneous conversational samples were recorded at the children's homes. The results are as follows. The error rates decreased with increasing age in all morphological contexts. Also, error percentages within an age group were significantly lower in lexical morphemes than in grammatical morphemes. The stopping of fricative sounds was the main error pattern in all morphological contexts and reduced as age increased. This research shows that articulation performance can differ significantly by morphological contexts. The present study provides data that can be used to identify the difficult context for articulatory evaluation and therapy of alveolar fricative sounds.

• Journal of the Korea Society of Computer and Information
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• v.20 no.10
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• pp.69-76
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• 2015

User's selection of music is largely influenced by private tastes as well as emotional states, and it is the unconsciousness projection of user's emotion. Therefore, we think user's emotional states to be music itself. In this paper, we try to grasp user's emotional states from music selected by users at a specific context, and we analyze the correlation between its context and user's emotional state. To get emotional states out of music, the proposed method extracts emotional words as the representative of music from lyrics of user-selected music through morphological analysis, and learns weights of linear classifier for each emotional features of extracted words. Regularities learned by classifier are utilized to calculate predictive weights of virtual music using weights of music chosen by other users in context similar to active user's context. Finally, we propose a method to recommend some pieces of music relative to user's contexts and emotional states. Experimental results shows that the proposed method is more accurate than the traditional collaborative filtering method.

• ALGAE
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• v.21 no.4
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• pp.349-375
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• 2006

The application of modern ecological, ultrastructural and molecular methods, aided by the cultivation of numerous cyanobacterial morphotypes, has substantially changed our knowledge of these organisms. It has led to major advances in cyanobacterial taxonomy and criteria for their phylogenetic classification. Molecular data provide basic criteria for cyanobacterial taxonomy; however, a correct phylogenetic system cannot be constructed without combining genetic data with knowledge from the previous 150 years research of cyanobacterial diversity. Thus, studies of morphological variation in nature, and modern morphological, ultrastructural, ecophysiological and biochemical characters need to be combined in a “polyphasic” approach. Taxonomic concepts for generic and infrageneric ranks are re-evaluated in light of combined phenotypic and molecular criteria. Despite their usefulness in experimental studies, the limitations of using strains from culture collections for systematic and nomenclatural purposes is highlighted. The need for a continual revision of strain identification and proper nomenclatural practice associated with either the bacteriological or botanical codes is emphasized. Recent advances in taxonomy are highlighted in the context of prospects for understanding cyanobacterial diversity from natural habitats, and the evolutionary and adaptational processes that cyanobacteria undergo.

• Mycobiology
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• v.49 no.3
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• pp.213-222
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• 2021

Two new species of Fulvifomes are described from specimens collected in rainforests of Nonggang Nature Reserve of southern China, based on morphological characteristics and molecular phylogenetic analysis of the internal transcribed spacer (ITS) and nuclear large subunit ribosomal DNA (nLSU) sequences. Fulvifomes nonggangensis sp. nov. is characterized by perennial, sessile and solitary basidiocarps, applanate pileus, small cystidioles of 9.9-15.4 × 2.9-3.5 ㎛, large pores of 5-6 per mm, a dimitic hyphal system, and broadly ellipsoid basidiospores of 4.3-5.3 × 3.3-4.2 ㎛. F. tubogeneratus sp. nov. is characterized by perennial, sessile, and imbricate basidiocarps, a duplex context, small pores of 7-8 per mm, a dimitic hyphal system, and ovoid to subglobose basidiospores of 5.72 × 5.00 ㎛.

• Journal of information and communication convergence engineering
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• v.17 no.3
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• pp.191-197
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• 2019

Morphological analysis is used for searching sentences and understanding context. As most morpheme analysis methods are based on predefined dictionaries, the problem of a target word not being registered in the given morpheme dictionary, the so-called unregistered word problem, can be a major cause of reduced performance. The current practical solution of such unregistered word problem is to add them by hand-write into the given dictionary. This method is a limitation that restricts the scalability and expandability of dictionaries. In order to overcome this limitation, we propose a novel method to automatically expand a dictionary by means of use-case analysis, which checks the validity of the unregistered word by exploring the use-cases through web crawling. The results show that the proposed method is a feasible one in terms of the accuracy of the validation process, the expandability of the dictionary and, after registration, the fast extraction time of morphemes.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.46-49
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• 1998

In this paper, we introduce the notion of intelligent communication by introducing a novel intelligent receiver model. This receiver is continually evolving and learns and improves in performance as it compiles its experience over time. In digital communication context, in a typical training mode, it jearns the concept of "1" as is deteriorated by arbitrary (not necessarily additive as is typically assumed) disturbance and /or modulation. After learning "1", in test mode, it classifies the received signal "1" and "0" almost completely. The intelligent receiver as implemented is grounded on the recently introduced Stochastic Morphological Sampling Theorem(SMST), a distribution-free result which gives theoretical bounds on the sample complexity(training size) needed for the required performance parameters such as accuracy($\varepsilon$) and confidence($\delta$). Based on this theorem, we demonstrate --almost irrespective of channel and modulation model-- the number of samples needed to learn the concept of "1" is not too "large" and the resulting universal receiver structure, that corresponding to classical Nearest Neighbor rule in Pattern Recognition Theory, is trivial. We check the surprising efficiency and validity of this model through some simple simulations. and validity of this model through some simple simulations.

• The KIPS Transactions:PartB
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• v.19B no.3
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• pp.195-200
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• 2012

In Korean, spelling change in various forms must be recovered into base forms in morphological analysis as well as part-of-speech (POS) tagging is difficult without morphological analysis because Korean is agglutinative. This is one of notorious problems in Korean morphological analysis and has been solved by morpheme recovery rules, which generate morphological ambiguity resolved by POS tagging. In this paper, we propose a morpheme recovery scheme based on machine learning methods like Na$\ddot{i}$ve Bayes models. Input features of the models are the surrounding context of the syllable which the spelling change is occurred and categories of the models are the recovered syllables. The POS tagging system with the proposed model has demonstrated the $F_1$-score of 97.5% for the ETRI tree-tagged corpus. Thus it can be decided that the proposed model is very useful to handle morpheme recovery in Korean.