Semantic networks based on titles of scientific papers
β Scribed by H.B.B. Pereira; I.S. Fadigas; V. Senna; M.A. Moret
- Book ID
- 103884582
- Publisher
- Elsevier Science
- Year
- 2011
- Tongue
- English
- Weight
- 648 KB
- Volume
- 390
- Category
- Article
- ISSN
- 0378-4371
No coin nor oath required. For personal study only.
β¦ Synopsis
In this paper we study the topological structure of semantic networks based on titles of papers published in scientific journals. It discusses its properties and presents some reflections on how the use of social and complex network models can contribute to the diffusion of knowledge. The proposed method presented here is applied to scientific journals where the titles of papers are in English or in Portuguese. We show that the topology of studied semantic networks are small-world and scale-free.
π SIMILAR VOLUMES
The main advantages of the semantic networks as formalism for knowledge representation are well known: simplicity, naturalness, visionless, and clarity. However, they have the following disadvantages: poor representation of arbitrary relations, insufficient expressiveness, unclear semantics, difficu
## Abstract Researchers begin new research by acquiring preβexisting explicit scientific knowledge that is potentially relevant to the research subject. In order to find some potentially relevant explicit scientific knowledge items, such as knowledge whose content is similar to the targeted researc
## Abstract Much research on contentβbased P2P searching for fileβsharing applications has focused on exploiting semantic relations between peers to facilitate searching. Current methods suggest __reactive__ ways to manage semantic relations: they rely on the usage of the underlying search mechanis