TY - GEN
T1 - Maps of computer science
AU - Fried, Daniel
AU - Kobourov, Stephen G.
PY - 2014
Y1 - 2014
N2 - We describe a practical approach for visual exploration of research papers. Specifically, we use the titles of papers from the DBLP database to create what we call maps of computer science (MoCS). Words and phrases from the paper titles are the cities in the map, and countries are created based on word and phrase similarity, calculated using co-occurence. With the help of heatmaps, we can visualize the profile of a particular conference or journal over the base map. Similarly, heatmap profiles can be made of individual researchers or groups such as a department. The visualization system also makes it possible to change the data used to generate the base map. For example, a specific journal or conference can be used to generate the base map and then the heatmap overlays can be used to show the evolution of research topics in the field over the years. As before, individual researchers or research group profiles can be visualized using heatmap overlays over a specific journal or conference base map. We outline a modular and extensible system for term extraction using natural language processing techniques, and show the applicability of methods of information retrieval to calculation of term similarity and creation of a topic map. The system is available at mocs.cs.arizona.edu.
AB - We describe a practical approach for visual exploration of research papers. Specifically, we use the titles of papers from the DBLP database to create what we call maps of computer science (MoCS). Words and phrases from the paper titles are the cities in the map, and countries are created based on word and phrase similarity, calculated using co-occurence. With the help of heatmaps, we can visualize the profile of a particular conference or journal over the base map. Similarly, heatmap profiles can be made of individual researchers or groups such as a department. The visualization system also makes it possible to change the data used to generate the base map. For example, a specific journal or conference can be used to generate the base map and then the heatmap overlays can be used to show the evolution of research topics in the field over the years. As before, individual researchers or research group profiles can be visualized using heatmap overlays over a specific journal or conference base map. We outline a modular and extensible system for term extraction using natural language processing techniques, and show the applicability of methods of information retrieval to calculation of term similarity and creation of a topic map. The system is available at mocs.cs.arizona.edu.
KW - Content Analysis and Indexing-Linguistic processing
KW - Information Search and RetrievalClustering
KW - Miscellaneous-Information visualization
KW - Topic visualization
KW - clustering
KW - term mapping
UR - http://www.scopus.com/inward/record.url?scp=84899554248&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84899554248&partnerID=8YFLogxK
U2 - 10.1109/PacificVis.2014.47
DO - 10.1109/PacificVis.2014.47
M3 - Conference contribution
AN - SCOPUS:84899554248
SN - 9781479928736
T3 - IEEE Pacific Visualization Symposium
SP - 113
EP - 120
BT - Proceedings - 2014 IEEE Pacific Visualization Symposium, PacificVis 2014
PB - IEEE Computer Society
T2 - 2014 7th IEEE Pacific Visualization Symposium, PacificVis 2014
Y2 - 4 March 2014 through 7 March 2014
ER -