Abstract | ||
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Cloud storage technology has becoming a cost-effective solution for organizations to manage their data in an efficient manner. However, the information stored in private clouds are not usually analyzed by organizations. This avoids organizations obtaining knowledge and taking advantages for data management. This paper presents a method for the extraction of semantic knowledge from private cloud storage repositories as well as the visualization of the acquired knowledge. In this approach, the knowledge extraction is based on the topic detection from repositories of text files (documents) stored in a private cloud storage, the extracted semantic knowledge is indexed as structured data, whereas an application, based on a topic index, enables the organization to visualize the knowledge in the form of graphs of topics per cloud storage location. The implementation of the proposed method shows the feasibility of this approach to get and visualize semantic knowledge extracted from documents. |
Year | DOI | Venue |
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2016 | 10.1145/3149235.3149239 | ENC'16: PROCEEDINGS OF THE SIXTEENTH MEXICAN INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE |
Keywords | Field | DocType |
Semantic knowledge,Topic detection,Graph Visualization,Cloud storage | Semantic memory,Graph drawing,Graph,Information retrieval,Computer science,Visualization,Artificial intelligence,Knowledge extraction,Data management,Data model,Cloud storage,Machine learning | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Ivan López-arévalo | 1 | 29 | 14.56 |
J. L. Gonzalez | 2 | 0 | 1.01 |
Leyla Alvarez-Medina | 3 | 0 | 0.34 |
Ana B. Rios-Alvarado | 4 | 28 | 6.51 |