• 제목/요약/키워드: Text Similarity

검색결과 277건 처리시간 0.024초

Word2Vec 학습을 통한 의미 기반 해외 유사 특허 검색 방안 (Identifying Similar Overseas Patent Using Word2Vec-Based Semantic Text Analytics)

  • 백민지;김남규
    • 한국IT서비스학회지
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    • 제17권2호
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    • pp.129-142
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    • 2018
  • Recently, the number of patent applications have been increasing rapidly every year as the importance of protecting intellectual property rights becomes more important. Patents must be inventive and have novelty. Especially, the novelty implies that the corresponding invention is not the same as the previous invention. To confirm the novelty, prior art search must be conducted before and after the application. The target of prior art search should include not only Korean patents but also foreign patents. Search of foreign patents should be supported by multilingual search techniques. However, a dictionary-based naive approach shows a limitation because some technical concepts are represented in different terms according to each nation. For example, a Korean term and a Japanese term may not be synonym even though they represent the same technical concept. In this paper, we propose a new method to map semantic similarity between technical terms in Korean patents and Japanese patents. To investigate different representations in each nation for the same technical concept, we identified and analyzed pairs of patents those are mutually connected with priority claim relationship. By performing an experiment with real-world data, we showed that our approach can reveal semantically similar technical terms in other language successfully.

구문트리 비고를 통한 프로그램 유형 복제 검사 (A Program-Plagiarism Checker using Abstract Syntax Tree)

  • 김영철;김성근;염세훈;최종명;유재우
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제30권7_8호
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    • pp.792-802
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    • 2003
  • 기존의 프로그램 유형 복제 검사 시스템들은 단순한 텍스트 기반의 프로그램 복제 검사나, 속성 및 토큰 스트링을 이용하여 복제 검사를 수행한다. 이 시스템들은 들여쓰기, 여백, 설명문과 같은 프로그램의 구문과 상관없는 프로그램 스타일에 어려움을 갖고 있다. 본 연구에서는 서로 다른 두 프로그램의 구문트리를 이용하여 복제 검사를 수행하는 모델을 제시한다. 구문트리를 이용한 프로그램 유형 복제 검사는 프로그램 스타일에 취약한 기존의 복제 검사 시스템의 단점을 극복할 수 있으며, 구문분석과 의미분석을 통해 프로그램의 구조적인 검사까지 수행할 수 있다는 장점을 가지고 있다. 또한 본 시스템은 인터넷이나 사이버 교육 체제에서 대량의 C/C+. 언어의 프로그램 복제 검사를 수행하기 위하여 AST 생성, 역파서 및 유사도 검사 알고리즘을 제시하며, 프로그램 복제 유형에 대해서 평가한다.

악곡구조 분석과 활용 (Music Structure Analysis and Application)

  • 서정범;배재학
    • 정보처리학회논문지B
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    • 제14B권1호
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    • pp.33-42
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    • 2007
  • 본 논문에서는 음악수사법에 기초하여 악곡요약을 구현할 새로운 악곡구조 분석 방법론을 소개한다. 이 방법론에서는 악곡 구성요소 간의 유사도 분석을 통해 악곡의 결합구조를 파악한 뒤, 결합구조에서 해당 곡이 취하고 있는 음악양식을 추정한다. 그 후 악식의 음악적 수사구조가 가지는 전통적인 특징과 표현기법을 근거로 악곡구조 안에서 주요선율을 추출한다. 문서요약의 경우와 같이 주어진 악보에서 추출된 주요선율은 그 곡의 요약이라고 간주할 수 있다. 개발한 악곡구조 분석 방법론은 대중음악 사례를 통하여 그 효용성을 가늠해 보았다.

제품 특징화를 위한 오피니언 문서의 클러스터링 기법 (An Opinion Document Clustering Technique for Product Characterization)

  • 장재영
    • 한국전자거래학회지
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    • 제19권2호
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    • pp.95-108
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    • 2014
  • 오피니언 마이닝은 문서로부터 의견을 추출하는 텍스트 마이닝의 응용분야로 현재 활발한 연구가 진행되고 있다. 대부분의 관련 연구는 특정 제품군에 대해서 주어진 특징별로 긍정과 부정 평가를 나누는 감성분류에 초점을 맞추고 있다. 하지만 제품별로 강조되는 특성들을 구별해내는 연구는 거의 이루어지고 있지 않다. 본 논문에서는 특성별로 오피니언 문서들을 분류하고, 이를 이용하여 특정 제품군에 대해서 제품별로 강조되는 특성들을 선별하는 기법을 제안한다. 제안된 기법에서는 텍스트 클러스터링을 활용하였으며, 새로운 유사도 계산 방식을 사용하였다. 또한 실험을 통하여 제안된 방법의 유용성을 증명하였다.

An Efficient Object Augmentation Scheme for Supporting Pervasiveness in a Mobile Augmented Reality

  • Jang, Sung-Bong;Ko, Young-Woong
    • Journal of Information Processing Systems
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    • 제16권5호
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    • pp.1214-1222
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    • 2020
  • Pervasive augmented reality (AR) technology can be used to efficiently search for the required information regarding products in stores through text augmentation in an Internet of Things (IoT) environment. The evolution of context awareness and image processing technologies are the main driving forces that realize this type of AR service. One of the problems to be addressed in the service is that augmented objects are fixed and cannot be replaced efficiently in real time. To address this problem, a real-time mobile AR framework is proposed. In this framework, an optimal object to be augmented is selected based on object similarity comparison, and the augmented objects are efficiently managed using distributed metadata servers to adapt to the user requirements, in a given situation. To evaluate the feasibility of the proposed framework, a prototype system was implemented, and a qualitative evaluation based on questionnaires was conducted. The experimental results show that the proposed framework provides a better user experience than existing features in smartphones, and through fast AR service, the users are able to conveniently obtain additional information on products or objects.

잠재디리클레할당을 이용한 한국학술지인용색인의 풍력에너지 문헌검토 (Review of Wind Energy Publications in Korea Citation Index using Latent Dirichlet Allocation)

  • 김현구;이제현;오명찬
    • 신재생에너지
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    • 제16권4호
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    • pp.33-40
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    • 2020
  • The research topics of more than 1,900 wind energy papers registered in the Korean Journal Citation Index (KCI) were modeled into 25 topics using latent directory allocation (LDA), and their consistency was cross-validated through principal component analysis (PCA) of the document word matrix. Key research topics in the wind energy field were identified as "offshore, wind farm," "blade, design," "generator, voltage, control," 'dynamic, load, noise," and "performance test." As a new method to determine the similarity between research topics in journals, a systematic evaluation method was proposed to analyze the correlation between topics by constructing a journal-topic matrix (JTM) and clustering them based on topic similarity between journals. By evaluating 24 journals that published more than 20 wind energy papers, it was confirmed that they were classified into meaningful clusters of mechanical engineering, electrical engineering, marine engineering, and renewable energy. It is expected that the proposed systematic method can be applied to the evaluation of the specificity of subsequent journals.

A Low-Cost Speech to Sign Language Converter

  • Le, Minh;Le, Thanh Minh;Bui, Vu Duc;Truong, Son Ngoc
    • International Journal of Computer Science & Network Security
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    • 제21권3호
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    • pp.37-40
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    • 2021
  • This paper presents a design of a speech to sign language converter for deaf and hard of hearing people. The device is low-cost, low-power consumption, and it can be able to work entirely offline. The speech recognition is implemented using an open-source API, Pocketsphinx library. In this work, we proposed a context-oriented language model, which measures the similarity between the recognized speech and the predefined speech to decide the output. The output speech is selected from the recommended speech stored in the database, which is the best match to the recognized speech. The proposed context-oriented language model can improve the speech recognition rate by 21% for working entirely offline. A decision module based on determining the similarity between the two texts using Levenshtein distance decides the output sign language. The output sign language corresponding to the recognized speech is generated as a set of sequential images. The speech to sign language converter is deployed on a Raspberry Pi Zero board for low-cost deaf assistive devices.

레시피 데이터 기반의 식재료 궁합 분석을 이용한 레시피 추천 시스템 구현 (Implementation of Recipe Recommendation System Using Ingredients Combination Analysis based on Recipe Data)

  • 민성희;오유수
    • 한국멀티미디어학회논문지
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    • 제24권8호
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    • pp.1114-1121
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    • 2021
  • In this paper, we implement a recipe recommendation system using ingredient harmonization analysis based on recipe data. The proposed system receives an image of a food ingredient purchase receipt to recommend ingredients and recipes to the user. Moreover, it performs preprocessing of the receipt images and text extraction using the OCR algorithm. The proposed system can recommend recipes based on the combined data of ingredients. It collects recipe data to calculate the combination for each food ingredient and extracts the food ingredients of the collected recipe as training data. And then, it acquires vector data by learning with a natural language processing algorithm. Moreover, it can recommend recipes based on ingredients with high similarity. Also, the proposed system can recommend recipes using replaceable ingredients to improve the accuracy of the result through preprocessing and postprocessing. For our evaluation, we created a random input dataset to evaluate the proposed recipe recommendation system's performance and calculated the accuracy for each algorithm. As a result of performance evaluation, the accuracy of the Word2Vec algorithm was the highest.

Research on Community Knowledge Modeling of Readers Based on Interest Labels

  • Kai, Wang;Wei, Pan;Xingzhi, Chen
    • Journal of Information Processing Systems
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    • 제19권1호
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    • pp.55-66
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    • 2023
  • Community portraits can deeply explore the characteristics of community structures and describe the personalized knowledge needs of community users, which is of great practical significance for improving community recommendation services, as well as the accuracy of resource push. The current community portraits generally have the problems of weak perception of interest characteristics and low degree of integration of topic information. To resolve this problem, the reader community portrait method based on the thematic and timeliness characteristics of interest labels (UIT) is proposed. First, community opinion leaders are identified based on multi-feature calculations, and then the topic features of their texts are identified based on the LDA topic model. On this basis, a semantic mapping including "reader community-opinion leader-text content" was established. Second, the readers' interest similarity of the labels was dynamically updated, and two kinds of tag parameters were integrated, namely, the intensity of interest labels and the stability of interest labels. Finally, the similarity distance between the opinion leader and the topic of interest was calculated to obtain the dynamic interest set of the opinion leaders. Experimental analysis was conducted on real data from the Douban reading community. The experimental results show that the UIT has the highest average F value (0.551) compared to the state-of-the-art approaches, which indicates that the UIT has better performance in the smooth time dimension.

A Dynamic Locality Sensitive Hashing Algorithm for Efficient Security Applications

  • Mohammad Y. Khanafseh;Ola M. Surakhi
    • International Journal of Computer Science & Network Security
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    • 제24권5호
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    • pp.79-88
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    • 2024
  • The information retrieval domain deals with the retrieval of unstructured data such as text documents. Searching documents is a main component of the modern information retrieval system. Locality Sensitive Hashing (LSH) is one of the most popular methods used in searching for documents in a high-dimensional space. The main benefit of LSH is its theoretical guarantee of query accuracy in a multi-dimensional space. More enhancement can be achieved to LSH by adding a bit to its steps. In this paper, a new Dynamic Locality Sensitive Hashing (DLSH) algorithm is proposed as an improved version of the LSH algorithm, which relies on employing the hierarchal selection of LSH parameters (number of bands, number of shingles, and number of permutation lists) based on the similarity achieved by the algorithm to optimize searching accuracy and increasing its score. Using several tampered file structures, the technique was applied, and the performance is evaluated. In some circumstances, the accuracy of matching with DLSH exceeds 95% with the optimal parameter value selected for the number of bands, the number of shingles, and the number of permutations lists of the DLSH algorithm. The result makes DLSH algorithm suitable to be applied in many critical applications that depend on accurate searching such as forensics technology.