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InfoVis 2017: IEEE Information Visualization Conference

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InfoVis
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투고 마감일:
2017-03-21
통보일:
2017-06-06
개최일:
2017-10-01
개최지:
Phoenix, Arizona, USA
조회: 47590   팔로우: 3   참가: 0

회반 지수 (CP-I)

53.5 / 100
전체 5,655개 중 954위 · 상위 17%

컴퓨터 그래픽스·멀티미디어 분야 148개 중 39위

학술적 인정 (35%) 데이터 없음 — 중립 기준값 50점으로 계산 —
투고 선별성 (20%) 데이터 없음 — 중립 기준값 50점으로 계산 —
개최 횟수 (20%)
81
커뮤니티 관심도 (10%)
24
공개 자료 충실도 (15%)
50

사용한 입력: 확인되는 개최 횟수: 19 · 회반에서 팔로우 중인 연구자: 3명 · 지난 24개월 동안 이 페이지를 연 연구자: 3명

공개 자료에서 빠진 항목: 역대 게재율 (+4.5) · 역대 회차 (+3.0)
주최자는 학회를 인증 신청한 뒤 이 페이지에서 바로 추가할 수 있습니다. 점수는 매일 밤 다시 계산됩니다. 이 점수를 올리는 방법

신뢰도 45% — 점수 중 중립 기준값이 아니라 실제 관측된 데이터에 근거한 비율. 이 점수는 어떻게 계산되나 · 전체 순위 보기 · 알고리즘 버전 1.1 · 산출일 2026-09-09

논문 모집

InfoVis 2017 (IEEE Information Visualization Conference) is an academic conference held in Phoenix, Arizona, USA on 2017-10-01. The paper submission deadline is 2017-03-21. Acceptance notifications are sent on 2017-06-06.

The IEEE Information Visualization conference (“InfoVis”) solicits research papers on a diverse set of topics related to information visualization. Broadly defined, information visualization is the design of visual data representations and interaction techniques that support human activities where the spatial layout of the visual representation is not a direct mapping of spatial relationships in the data. Papers may contribute novel visual encoding or interaction techniques, evaluations of InfoVis techniques and tools, models or theories related to InfoVis, systems that support visual data analysis, or applications of information visualization to domain-specific problems. None of these guidelines are in any way prescriptive; in fact, many successful papers combine two contribution types, and some of the very best papers often combine several. Please note that topics primarily involving spatial data (such as scalar, vector and tensor fields) might be a better match for the IEEE SciVis Conference at IEEE VIS. Similarly, topics that clearly focus on visual analytics, e.g., computational solutions facilitated by visual interfaces to support analysis, might be a better match for the IEEE VAST Conference, also at IEEE VIS. Papers chairs reserve the right to move papers between conferences based on its topic and perceived fit. Topics Research contributions are welcomed across a range of topics including, but not limited to: Information visualization techniques for graphs (networks), trees (hierarchies), and other relational data high-dimensional data and dimensionality reduction multivariate data heterogeneous data personal or social data (health, energy, finance, fitness, email, etc.) text and documents non-numeric data (categorical data, nominal data, etc.) non-expert audiences causality and uncertainty data time-series & temporal event data spatial data, particularly visualized with a new spatial mapping combinations of abstract and spatial data streaming or time-varying data very large datasets Interaction techniques for visualizations or for supporting the data analysis process, including recordkeeping, sensemaking, and storytelling collaboration support (both co-located and distributed) integration of visualization with other software tools post-WIMP interactions (pen, touch, speech, gestures, etc.) focus + context and overview + detail methods zooming, navigation, and distortion techniques brushing and linking coordinated multiple views data labeling, editing, and annotation Integration of visualizations into the context of use, including visual design and aesthetics minimal attention contexts (e.g. ambient displays, second screens) mobile and ubiquitous applications public environments Information visualization fundamentals and methodologies: novel algorithms and mathematics taxonomies and models research methodology, discussions, and frameworks cognition and perception Evaluation: task and requirements analysis metrics and benchmarks qualitative and quantitative evaluation laboratory and field studies novel evaluation methods usability studies and focus groups case studies (involving real users) replications of past studies that validate or contradict key findings Applied information visualization: reports of information visualization in domains where it has impact using information visualization for education and teaching design studies
최종 수정: Dou Sun ()

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관련 저널

CCF정식 명칭영향력 지수출판사ISSN
Visualization in EngineeringSpringer2213-7459
Computing and Visualization in ScienceSpringer1432-9360
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.9Elsevier0167-8655
BPattern Recognition7.6Elsevier0031-3203

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