• 제목/요약/키워드: number word

검색결과 706건 처리시간 0.025초

한의학 고문헌 텍스트 분석을 위한 비지도학습 기반 단어 추출 방법 비교 (Comparison of Word Extraction Methods Based on Unsupervised Learning for Analyzing East Asian Traditional Medicine Texts)

  • 오준호
    • 대한한의학원전학회지
    • /
    • 제32권3호
    • /
    • pp.47-57
    • /
    • 2019
  • Objectives : We aim to assist in choosing an appropriate method for word extraction when analyzing East Asian Traditional Medical texts based on unsupervised learning. Methods : In order to assign ranks to substrings, we conducted a test using one method(BE:Branching Entropy) for exterior boundary value, three methods(CS:cohesion score, TS:t-score, SL:simple-ll) for interior boundary value, and six methods(BExSL, BExTS, BExCS, CSxTS, CSxSL, TSxSL) from combining them. Results : When Miss Rate(MR) was used as the criterion, the error was minimal when the TS and SL were used together, while the error was maximum when CS was used alone. When number of segmented texts was applied as weight value, the results were the best in the case of SL, and the worst in the case of BE alone. Conclusions : Unsupervised-Learning-Based Word Extraction is a method that can be used to analyze texts without a prepared set of vocabulary data. When using this method, SL or the combination of SL and TS could be considered primarily.

멀티플렉스 모바일 서비스 품질이 온라인 구전의도에 미치는 영향력 분석: 이용 즐거움의 매개효과와 성별의 조절효과를 중심으로 (Analyzing The Influence of Multiplex Mobile Service Quality on Online Word of Mouth: Focusing on the Mediating Effect of Use Enjoyment and the Moderating Effect of Gender)

  • 이한솔;김현철
    • Journal of Information Technology Applications and Management
    • /
    • 제25권4호
    • /
    • pp.123-143
    • /
    • 2018
  • The domestic multiplex industry provides consumers with a choice of movies and a variety of contents and entertainment facilities and services. In addition, the number of movie theaters with the significant market potential is also steadily increasing in the competitive multiplex market environment. For the analysis, we conducted research on 300 adolescents who have experienced using domestic multiplex mobile service within the recent year. This study examined the structural relationship among the multi-dimensional mobile service quality of multiple, enjoyment of use, and online word of mouth intention. Also, it explored the mediating effect of enjoyment of use and the moderating effect of gender in the structural model. As a result, the mobile service quality of multiplex has a significant effect on the online word of mouth intention through the enjoyment of use. However, there was no moderating effect of gender of participating adolescents in the relationships. Based on the analysis of empirical results, this study discussed a series of theocratical and practical implications for the marketing strategies of multiplex in the highly competitive market.

The Impact of Corporate Greenwashing Behavior on Consumers' Purchase Intentions of Green Electronic Devices: An Empirical Study in Vietnam

  • NGUYEN, Thi Thu Huong;NGUYEN, Kieu Oanh;CAO, Tuan Khanh;LE, Viet Anh
    • The Journal of Asian Finance, Economics and Business
    • /
    • 제8권8호
    • /
    • pp.229-240
    • /
    • 2021
  • The environment friendly lifestyle and the green product trend have motivated corporates to develop and adopt sustainable business practices. However, an increasing number of corporations have engaged in greenwashing practices to create the appearance of environmental responsibility. By employing the theory of reasoned action, the paper investigated a model linking corporate greenwashing and consumers' green purchase intentions with the mediating role of green trust and green word-of-mouth about green electronic devices in Vietnam. Using an online survey via Email, Zalo, and Wechat, data was obtained from 308 Vietnamese consumers who have been purchasing green electronic devices. Based on the responses of the participants from the questionnaires conducted, data analysis was conducted by using SEM in AMOS version 23. This investigation shows that corporate greenwashing negatively affects consumers' green trust, green word-of-mouth, and their green buying intentions. Additionally, the paper verifies that green trust and green word-of-mouth mediate the relationships between greenwashing and consumers' green purchase intentions. These results reinforce the extant understanding of greenwashing and its consequences. Finally, the study not only stimulates future research but serves as a reference for business managers, scholars, and students who are interested on the topic of environmental sustainability, new product development, and green brands.

Incorporating Deep Median Networks for Arabic Document Retrieval Using Word Embeddings-Based Query Expansion

  • Yasir Hadi Farhan;Mohanaad Shakir;Mustafa Abd Tareq;Boumedyen Shannaq
    • Journal of Information Science Theory and Practice
    • /
    • 제12권3호
    • /
    • pp.36-48
    • /
    • 2024
  • The information retrieval (IR) process often encounters a challenge known as query-document vocabulary mismatch, where user queries do not align with document content, impacting search effectiveness. Automatic query expansion (AQE) techniques aim to mitigate this issue by augmenting user queries with related terms or synonyms. Word embedding, particularly Word2Vec, has gained prominence for AQE due to its ability to represent words as real-number vectors. However, AQE methods typically expand individual query terms, potentially leading to query drift if not carefully selected. To address this, researchers propose utilizing median vectors derived from deep median networks to capture query similarity comprehensively. Integrating median vectors into candidate term generation and combining them with the BM25 probabilistic model and two IR strategies (EQE1 and V2Q) yields promising results, outperforming baseline methods in experimental settings.

스토리기반 저작물에서 감정어 분류에 기반한 등장인물의 감정 성향 판단 (Detection of Character Emotional Type Based on Classification of Emotional Words at Story)

  • 백영태
    • 한국컴퓨터정보학회논문지
    • /
    • 제18권9호
    • /
    • pp.131-138
    • /
    • 2013
  • 본 논문에서는 등장인물이 대사에서사용한감정어를 이용하여 등장인물의 감정 유형을 분류하는 방법을 제안하고 성능을 평가한다. 감정 유형은 긍정, 부정, 중립의 3 종류로 분류하며, 등장인물이 사용한 감정어를 누적하여 3 종류의 감정 유형 중에 어디에 속하는지를 파악한다. 대사로부터 감정어를 추출하기 위해 WordNet 기반의 감정어 추출 방법을 제안하고 감정어가 가진 감정 성분을 벡터로 표현하는 방식을 제안한다. WordNet은 영어 단어 간에 상위어와 하위어, 유사어 등의 관계로 연결된 네트워크 구조의 사전이다. 이 네트워크 구조에서 최상위의 감정항목과의 거리를 계산하여 단어별감정량을 계산하여 대사를 30 차원의 감정벡터로 표현한다. 등장인물별로 추출된 감정 벡터 성분들을 긍정, 부정, 중립의 3가지 차원으로 축소하여 표현한 후, 등장인물의 감정 성향이 어떻게 나타나는지를 추출한다. 또한 감정 성향의 추출 성능에 대해 헐리우드 영화 4개의 영화에서 12명의 등장인물을 선정하여 평가하여 제안한 방법의 효율성을 측정하였다. 대사는 영어로 이루어진 대사만을 사용하였다. 추출된 감정 성향 판단 성능은 75%의 정확도로 우수한 추출 성능을 나타내었다.

한국어 형태소 분석을 위한 효율적 기분석 사전의 구성 방법 (Construction of an Efficient Pre-analyzed Dictionary for Korean Morphological Analysis)

  • 곽수정;김보겸;이재성
    • 정보처리학회논문지:소프트웨어 및 데이터공학
    • /
    • 제2권12호
    • /
    • pp.881-888
    • /
    • 2013
  • 기분석 사전은 형태소 분석기의 속도와 정확도를 향상시키고, 과분석을 줄이기 위해 사용된다. 하지만 기분석 사전에 저장된 어절 중에 저장된 형태소 분석 결과가 부족한 어절, 즉 불충분 분석 어절이 존재할 경우 오히려 형태소 분석기의 정확도를 떨어뜨리는 원인으로 작용할 수 있다. 본 논문에서는 세종 형태 분석 말뭉치(문어체, 2011)를 이용해 말뭉치의 크기와 어절 빈도의 변화에 따라 사전의 정답 제시율이 변화하는 양상을 측정하였다. 그리고 통계기반의 형태소 분석기인 SMA와 기분석 사전을 결합한 통합 시스템을 구성하여 기분석 사전의 충분 분석률이 99.82% 이상일 때 시스템 전체 성능이 향상되는 것을 확인하였다. 또한 160만 어절의 말뭉치를 이용할 때는 32회 이상 출현한 어절로, 630만 어절로 구성된 말뭉치를 이용할 때는 64회 이상 출현한 어절로 사전을 구성하는 것이 통합 시스템의 성능을 가장 높게 할 수 있었다.

SNS를 통한 구전 효과가 영화 흥행에 미치는 영향 -<써니>의 사례를 중심으로- (Influence of the Word-of-Mouth Effect through SNS on the Movie Performance -Focused on the Case of <Sunny>-)

  • 박선영
    • 한국콘텐츠학회논문지
    • /
    • 제12권7호
    • /
    • pp.40-53
    • /
    • 2012
  • 과거에는 영화 흥행을 좌우하는 요소로 감독, 스타 배우, 개봉 스크린 수, 온라인 평점, 배급사 등을 들었다. 그러나 구전 효과의 등장으로 이러한 공식에도 변화가 초래되었는데, 인터넷과 스마트폰이 널리 보급된 현 시점에서는 구전 효과의 영향력이 점점 더 강해지고 있다. 저자는 구전 효과가 이루어지는 매개체 중 하나인 SNS에 주목하여, SNS가 영화 흥행에 영향을 미친 실제 사례에 대하여 조명해 보려 한다. 작년에 크게 흥행했던 영화 중에서 SNS의 효과를 톡톡히 보았다고 일컬어지는 <써니>의 제작 및 상영 과정에 동반되었던 SNS 활동을 분석해 보는 것이다. 개봉 전, 개봉 초기, 성숙기로 시기를 구분하여 SNS를 통한 구전 활동을 살펴봄으로써, SNS 활동의 성공 사례를 통해 영화 흥행과 관련된 하나의 이정표를 제시하는데 이 글의 의의가 있다.

Word2Vec를 이용한 토픽모델링의 확장 및 분석사례 (Expansion of Topic Modeling with Word2Vec and Case Analysis)

  • 윤상훈;김근형
    • 한국정보시스템학회지:정보시스템연구
    • /
    • 제30권1호
    • /
    • pp.45-64
    • /
    • 2021
  • Purpose The traditional topic modeling technique makes it difficult to distinguish the semantic of topics because the key words assigned to each topic would be also assigned to other topics. This problem could become severe when the number of online reviews are small. In this paper, the extended model of topic modeling technique that can be used for analyzing a small amount of online reviews is proposed. Design/methodology/approach The extended model of being proposed in this paper is a form that combines the traditional topic modeling technique and the Word2Vec technique. The extended model only allocates main words to the extracted topics, but also generates discriminatory words between topics. In particular, Word2vec technique is applied in the process of extracting related words semantically for each discriminatory word. In the extended model, main words and discriminatory words with similar words semantically are used in the process of semantic classification and naming of extracted topics, so that the semantic classification and naming of topics can be more clearly performed. For case study, online reviews related with Udo in Tripadvisor web site were analyzed by applying the traditional topic modeling and the proposed extension model. In the process of semantic classification and naming of the extracted topics, the traditional topic modeling technique and the extended model were compared. Findings Since the extended model is a concept that utilizes additional information in the existing topic modeling information, it can be confirmed that it is more effective than the existing topic modeling in semantic division between topics and the process of assigning topic names.

Bi-directional Maximal Matching Algorithm to Segment Khmer Words in Sentence

  • Mao, Makara;Peng, Sony;Yang, Yixuan;Park, Doo-Soon
    • Journal of Information Processing Systems
    • /
    • 제18권4호
    • /
    • pp.549-561
    • /
    • 2022
  • In the Khmer writing system, the Khmer script is the official letter of Cambodia, written from left to right without a space separator; it is complicated and requires more analysis studies. Without clear standard guidelines, a space separator in the Khmer language is used inconsistently and informally to separate words in sentences. Therefore, a segmented method should be discussed with the combination of the future Khmer natural language processing (NLP) to define the appropriate rule for Khmer sentences. The critical process in NLP with the capability of extensive data language analysis necessitates applying in this scenario. One of the essential components in Khmer language processing is how to split the word into a series of sentences and count the words used in the sentences. Currently, Microsoft Word cannot count Khmer words correctly. So, this study presents a systematic library to segment Khmer phrases using the bi-directional maximal matching (BiMM) method to address these problematic constraints. In the BiMM algorithm, the paper focuses on the Bidirectional implementation of forward maximal matching (FMM) and backward maximal matching (BMM) to improve word segmentation accuracy. A digital or prefix tree of data structure algorithm, also known as a trie, enhances the segmentation accuracy procedure by finding the children of each word parent node. The accuracy of BiMM is higher than using FMM or BMM independently; moreover, the proposed approach improves dictionary structures and reduces the number of errors. The result of this study can reduce the error by 8.57% compared to FMM and BFF algorithms with 94,807 Khmer words.

Distribution of a Soft Drink Brand Communication on Brand Image with e-WOM as a Mediating Role on Indonesians Gen Z

  • SHIDDIQI, Muhammad fajar;LI, Sin;SUHARI, Umaidi;HIDAYAT, Zinggara;MANI, La
    • 유통과학연구
    • /
    • 제21권1호
    • /
    • pp.85-93
    • /
    • 2023
  • Purpose: This research is intended to analyze how distribution of brand communication of a Soft Drink brand on brand image mediated through electronic word of mouth on packaged carbonated drink in Indonesian Gen-Z. This research also aims to find out how electronic word of mouth can have a role in creating a brand image for Indonesia Gen-Z. Research design, data and methodology: This research is using a quantitative approach with purposive sampling technique, a survey was conduct online and the number of samples being 384 responders who are spread all over Indonesia. The questionnaire construct was designed based on several variables, such as brand communication, brand image, and e-WOM. E-WOM was positioned as a mediating variable in this research. Brand Communication indicators consist of event and experience, public relation and publicity, direct marketing and personal selling. Meanwhile brand image consists of Attributes, Benefits, and Attitudes. E-WOM indicators consist of intensity, balance of opinion, and content. Results: The result of this research being (1) There is a significant influence between brand communication and brand image. (2) There is a significant influence between brand communication and electronic word-of-mouth. And (3) There is a significant influence between brand communication and brand image mediated through electronic word-of-mouth. Conclusion: The findings of this research prove that there is significant influence between brand communication, brand image and electronic word-of-mouth, this study also provide several information about how other factor affect the distribution of brand communication.