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KTimeML: Specification of Temporal and Event Expressions in Korean Text
TLDR
This paper presents the problems and solutions for porting TimeML to Korean as a part of the Korean TARSQI Project. Expand
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Language-Specific Sentiment Analysis in Morphologically Rich Languages
TLDR
In this paper, we propose language-specific methods of sentiment analysis in morphologically rich languages. Expand
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KR-BERT: A Small-Scale Korean-Specific Language Model
TLDR
We trained a Korean-specific model KR-BERT, utilizing a smaller vocabulary and dataset. Expand
  • 5
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Schema and constraints-based matching and merging of Topic Maps
TLDR
We propose a multi-strategic matching and merging approach to find correspondences between ontologies based on the syntactic or semantic characteristics and constraints of the Topic Maps. Expand
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FolksoViz: A Semantic Relation-Based Folksonomy Visualization Using the Wikipedia Corpus
TLDR
We propose a technique, Folk-soViz, for automatically deriving semantic relations between tags and for visualizing the tags and their relations. Expand
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Identification of Implicit Topics in Twitter Data Not Containing Explicit Search Queries
TLDR
We found that Tweet Serialization can be detected using various criteria such as reply relations between users, presence of discourse or continuation markers, and temporal proximity under the same authorship. Expand
  • 5
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Effective Use of Linguistic Features for Sentiment Analysis of Korean
TLDR
We propose a new linguistic approach for sentiment analysis of Korean. Expand
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Getting Information from Documents You Cannot Read: An Interactive Cross-Language Text Retrieval and Summarization System
TLDR
In this paper we discuss research designed to investigate the ability of users to find information in texts written in languages unknown to them. Expand
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Tag Sense Disambiguation for Clarifying the Vocabulary of Social Tags
TLDR
We propose a tag sense disambiguating method, called Tag Sense Disambigu-ation (TSD), which works in the social tagging environment. Expand
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Applying Graph-based Keyword Extraction to Document Retrieval
TLDR
This paper proposes a keyword extraction process, based on the PageRank algorithm, to reduce noise of input data for measuring semantic similarity. Expand
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