• Title/Summary/Keyword: Precision-recall

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A Hangul Document Image Retrieval System Using Rank-based Recognition (웨이브렛 특징과 순위 기반 인식을 이용한 한글 문서 영상 검색 시스템)

  • Lee Duk-Ryong;Kim Woo-Youn;Oh Il-Seok
    • The Journal of the Korea Contents Association
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    • v.5 no.2
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    • pp.229-242
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    • 2005
  • We constructed a full-text retrieval system for the scanned Hangul document images. The system consists of three parts; preprocessing, recognition, and retrieval components. The retrieval algorithm uses recognition results up to k-ranks. The algorithm is not only insensitive to the recognition errors, but also has the advantage of user-controllable recall and precision. For the objective performance evaluation, we used the scanned images of the Journal of Korea Information Science Society provided by KISTI. The system was shown to be practical through theevaluationofrecognitionandretrievalrates.

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Video Shot Boundary Detection Using Correlation of Luminance and Edge Information (명도와 에지정보의 상관계수를 이용한 비디오샷 경계검출)

  • Yu, Heon-U;Jeong, Dong-Sik;Na, Yun-Gyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.7 no.4
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    • pp.304-308
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    • 2001
  • The increase of video data makes the demand of efficient retrieval, storing, and browsing technologies necessary. In this paper, a video segmentation method (scene change detection method, or shot boundary detection method) for the development of such systems is proposed. For abrupt cut detection, inter-frame similarities are computed using luminance and edge histograms and a cut is declared when the similarities are under th predetermined threshold values. A gradual scene change detection is based on the similarities between the current frame and the previous shot boundary frame. A correlation method is used to obtain universal threshold values, which are applied to various video data. Experimental results show that propose method provides 90% precision and 98% recall rates for abrupt cut, and 59% precision and 79% recall rates for gradual change.

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Objective Evaluation of Background Subtraction Algorithms for Soccer Video Analysis: An Experimental Comparative Study (축구 동영상 분석을 위한 배경 분리 알고리즘들의 정량적 비교 평가에 관한 연구)

  • Jung, Chanho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.42 no.1
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    • pp.42-45
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    • 2017
  • In this letter, we present an experimental comparative study of background subtraction algorithms for soccer video analysis. We investigated five different background subtraction algorithms under the same experimental setup. For the quantitative comparison, we employed the precision, recall, and F-measure. We believe that this comprehensive comparative study serves as a reference point and guide for developers and practitioners in choosing an appropriate background subtraction algorithm adopted for building intelligent soccer video analysis systems.

Comparative Study of Various Persian Stemmers in the Field of Information Retrieval

  • Moghadam, Fatemeh Momenipour;Keyvanpour, MohammadReza
    • Journal of Information Processing Systems
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    • v.11 no.3
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    • pp.450-464
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    • 2015
  • In linguistics, stemming is the operation of reducing words to their more general form, which is called the 'stem'. Stemming is an important step in information retrieval systems, natural language processing, and text mining. Information retrieval systems are evaluated by metrics like precision and recall and the fundamental superiority of an information retrieval system over another one is measured by them. Stemmers decrease the indexed file, increase the speed of information retrieval systems, and improve the performance of these systems by boosting precision and recall. There are few Persian stemmers and most of them work based on morphological rules. In this paper we carefully study Persian stemmers, which are classified into three main classes: structural stemmers, lookup table stemmers, and statistical stemmers. We describe the algorithms of each class carefully and present the weaknesses and strengths of each Persian stemmer. We also propose some metrics to compare and evaluate each stemmer by them.

A Comparative Study on Collaborative Filtering Algorithm (협업 필터링 알고리즘에 관한 비교연구)

  • Li, Jiapei;Li, Xiaomeng;Lee, HyunChang;Shin, SeongYoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.151-153
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    • 2017
  • In recommendation system, collaborative filtering is the most important algorithm. Collaborative filtering is a method of making automatic predictions about the interests of a user by collecting preferences or taste information from many users. In this paper five algorithms were used. Metrics such as Recall-Precision, FPR-TPR,RMSE, MSE, MAE were calculated. From the result of the experiment, the user-based collaborative filtering was the best approach to recommend movies to users.

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A Study on measuring techniques of retrieval effectiveness (검색효율 측정척도에 관한 연구)

  • Yoon Koo Ho
    • Journal of the Korean Society for Library and Information Science
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    • v.16
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    • pp.177-205
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    • 1989
  • Retrieval effectiveness is the principal criteria for measuring the performance of an information retrieval system. This paper deals with the characteristics of 'relevance' of information and various measuring techniques of retrieval effectivess. The outlines of this study are as follows: 1) Relevance decision for evaluation should be devided into the user-oriented and the system-oriented decisions. 2) The recall-precision measure seems to be user-oriented, and the recall-fallout measure to be system-oriented. 3) Many of composite measures can not be justified III any rational manner unfortunately. 4) The Swets model has demonstrated that it yields, in general, a straight line instead of a curve of varying curvature and emphasized the fundamentally probabilistic nature of information retrieval. 5) The Cooper model seems to be a good substitute for precision and a useful measure for systems which ranked documents. 6) The Rocchio model were proposed for the evaluation of retreval systems which ranked documents, and were designed to be independent of cut-off. 7) The Cawkell model suggested that the Shannon's equation for entropy can be applied to measuring of retrieval effectiveness.

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Development of Ontology for Thai Country Songs

  • Thunyaluk, Jaitiang;Malee, Kabmala;Wirapong, Chansanam
    • Journal of Information Science Theory and Practice
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    • v.11 no.1
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    • pp.79-88
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    • 2023
  • This study aimed to develop an ontology for Thai country songs by using the seven steps of an ontology development process. Hozo-Ontology Editor software and Ontology Application Management Framework were tools used in this study. Nine classes of ontology were identified: song, singer, emotion, author, language used, language type, song style, original, and content, and it was found that the song class had a relationship with all of the other classes. The developed ontology was evaluated by seeking opinions from experts in the field of Thai country songs, who agreed that the ontology was highly effective. Additionally, the evaluation employed the knowledge retrieval concept, and the precision, recall, and overall effectiveness were measured, with a precision of 92.59%, a recall of 86.21%, and an overall effectiveness (F-measure) of 89.28%. These results indicate that the developed ontology is highly effective in describing the scope of knowledge of Thai country songs.

Improving Recall for Context-Sensitive Spelling Correction Rules Through Integrated Constraint Loosening Method (통합적 제약완화 방식을 통한 한국어 문맥의존 철자오류 교정규칙의 재현율 향상)

  • Choi, Hyunsoo;Yoon, Aesun;Kwon, Hyukchul
    • KIISE Transactions on Computing Practices
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    • v.21 no.6
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    • pp.412-417
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    • 2015
  • Context-sensitive spelling errors (CSSE) are hard to correct, since they are perfect words when analyzed alone. Determined only by considering the semantic and syntactic relations of their context, CSSEs affect largely the performance of spelling and grammar checkers. The existing Korean Spelling and Grammar Checker (KSGC 4.5) adopts a rule-based method, which uses hand-made correction rules for CSSEs. Using rule-based method, the KSGC 4.5 is designed to obtain the very high precision, which results in the extremely low recall. In this paper, we integrate our previous works that control the CSSE correction rules, in order to improve the recall without sacrificing the precision. In addition to the integration, facultative insertion of adverbs and conjugation suffix of predicates are also considered, as for constraint-loosening linguistic features.

An Experimental Study on the Retrieval Efficiency of the FRBR Based Bibliographic Retrieval System (FRBR 모형 기반 서지검색시스템의 검색 효율성 평가 연구)

  • Kim, Hyun-Hee
    • Journal of Korean Library and Information Science Society
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    • v.38 no.3
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    • pp.223-246
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    • 2007
  • This study examines the retrieval efficiency of the FRBR-based bibliographic retrieval system. To do this, we built two experimental retrieval systems(a FRBR-based system constructed through FRBRizing algorithms and an OPAC-based retrieval system) using 387 music materials coded in a KORMARC format. Next, we set up six hypotheses and compared these two systems in terms of recall, precision, and retrieval time using 28 participants and a questionnaire with 12 queries. The results show that the average recall value of the FRBR-based system Is higher than that of the OPAC system regardless of query types and the average precision and retrieval time values of manifestation queries of the OPAC system is more efficient that those of the FRBR-based system. This study results can be used to customize digital library interfaces as well as to improve the retrieval efficiency of the bibliographic retrieval system.

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Automatic Detection of Highlights in Soccer videos based on analysis of scene structure (축구 동영상에서의 장면 구조 분석에 기반한 자동적인 하이라이트 장면 검출)

  • Park, Ki-Tae;Moon, Young-Shik
    • The KIPS Transactions:PartB
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    • v.14B no.1 s.111
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    • pp.1-4
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    • 2007
  • In this paper, we propose an efficient scheme for automatically detecting highlight scenes in soccer videos. Highlights are defined as shooting scenes and goal scenes. Through the analysis of soccer videos, we notice that most of highlight scenes are shown around the goal post area. It is also noticed that the TV camera zooms in a setter player or spectators after the highlight stones. Detection of highlight scenes for soccer videos consists of three steps. The first step is the extraction of the playing field using a statistical threshold. The second step is the detection of goal posts. In the final step, we detect a zooming of a soccer player or spectators by using connected component labeling of non-playing field. In order to evaluate the performance of our method, the precision and the recall are computed. Experimental results have shown the effectiveness of the proposed method, with 95.2% precision and 85.4% recall.