Name
Abstract | ||
|---|---|---|
Academic work: grading student assignments or conducting literature surveys entails extensive reading, which is both a time consuming and cognitively demanding task. The challenge increases proportionally with the increase of volume of the textual content. In this paper, we propose a novel approach to visualization of textual data that depicts information on a continuum (temporal or spatial) allowing inferences to be made about thematic organization of a document and its structure. Our visualization method—termed ThemeTrack—creates a visual map: delineating key themes and tracking their presence throughout the text, highlighting their variations and relationships. It aims to make the review of textual data more efficient. To assess the viability of the proposed approach, a series of experiments were conducted using graduate-level theses and published articles in the peer-reviewed journals. The applications of the proposed method are discussed and the real-word examples are provided. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ICALT.2017.24 | 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT) |
Keywords | Field | DocType |
data analytics,knowledge retrieval,technology-enhanced assessment,text mining,visualization methods for learning | Pragmatics,Computer science,Extensive reading,Visual analytics,Thematic map,Natural language processing,Artificial intelligence,Data visualization,Information retrieval,Information visualization,Visualization,Multimedia,Semantics | Conference |
ISSN | ISBN | Citations |
2161-3761 | 978-1-5386-3871-2 | 0 |
PageRank | References | Authors |
0.34 | 10 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexander Amigud | 1 | 3 | 1.77 |
| Joan Arnedo | 2 | 134 | 21.88 |
| Thanasis Daradoumis | 3 | 421 | 44.65 |
| Ana-elena Guerrero | 4 | 14 | 7.27 |