TY - GEN
T1 - The 4D world map system with semantic spatiotemporal analyzers
AU - Sasaki, Shiori
AU - Takahashi, Yusuke
AU - Kiyoki, Yasushi
PY - 2010
Y1 - 2010
N2 - This paper presents a design and implementation for the "4D World Map System," a knowledge representation system which enables semantic, temporal and spatial analysis of documents, and integrates and visualizes the analyzed results as a 4-dimentional dynamic historical atlas (4D World Map Set). The main feature of this system is to create various context-dependent patterns of historical/cultural stories according to a user's viewpoints dynamically. This system generates multiple views of semantic and temporal-spatial relationships among documents of the humanities and social sciences. This system organizes the relationships among documents into various historical/cultural stories by a user's viewpoints. A semantic associative search method is applied to this system for realizing the concept that "semantics" of words, documents, and events vary according to the "context". Semantically-evaluated and analyzed document data are also mapped dynamically onto a time-series multi-geographical space. This system provides high visibility of semantic correlations between documents in time series variation with geographic information. In this paper, we also show several experiments by using news articles and International Relations documents to clarify the feasibility of the system.
AB - This paper presents a design and implementation for the "4D World Map System," a knowledge representation system which enables semantic, temporal and spatial analysis of documents, and integrates and visualizes the analyzed results as a 4-dimentional dynamic historical atlas (4D World Map Set). The main feature of this system is to create various context-dependent patterns of historical/cultural stories according to a user's viewpoints dynamically. This system generates multiple views of semantic and temporal-spatial relationships among documents of the humanities and social sciences. This system organizes the relationships among documents into various historical/cultural stories by a user's viewpoints. A semantic associative search method is applied to this system for realizing the concept that "semantics" of words, documents, and events vary according to the "context". Semantically-evaluated and analyzed document data are also mapped dynamically onto a time-series multi-geographical space. This system provides high visibility of semantic correlations between documents in time series variation with geographic information. In this paper, we also show several experiments by using news articles and International Relations documents to clarify the feasibility of the system.
KW - 4-Dimensional Visualization
KW - Knowledge Base
KW - Learning Support Systems
KW - Multi-Context Mining
KW - Semantic Associative Search
KW - Temporal-Spatial Representation
UR - http://www.scopus.com/inward/record.url?scp=77950977730&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77950977730&partnerID=8YFLogxK
U2 - 10.3233/978-1-60750-477-1-1
DO - 10.3233/978-1-60750-477-1-1
M3 - Conference contribution
AN - SCOPUS:77950977730
SN - 9781607500896
T3 - Frontiers in Artificial Intelligence and Applications
SP - 1
EP - 18
BT - Information Modelling and Knowledge Bases XXI
PB - IOS Press
ER -