Name
Abstract | ||
|---|---|---|
Social Web Media is one of the most important sources of big data to extract and acquire new knowledge. Social Networks have become an important environment where users provide information of their preferences and relationships. This information can be used to measure the influence of ideas and the society opinions in real time, being very useful on several fields and research areas such as marketing campaigns, financial prediction or public healthcare among others. Recently, the research on artificial intelligence techniques applied to develop technologies allowing monitoring web data sources for detecting public health events has emerged as a new relevant discipline called Epidemic Intelligence. Epidemic Intelligence Systems are nowadays widely used by public health organizations like monitoring mechanisms for early detection of disease outbreaks to reduce the impact of epidemics. This paper presents a survey on current data mining applications and web systems based on web data for public healthcare over the last years. It tries to take special attention to machine learning and data mining techniques and how they have been applied to these web data to extract collective knowledge from Twitter |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-10422-5_36 | Studies in Computational Intelligence |
Field | DocType | Volume |
Data science,Public health,Web system,Social network,Social web,Collective intelligence,Outbreak,Public healthcare,Big data,Medicine | Conference | 570.0 |
ISSN | Citations | PageRank |
1860-949X | 1 | 0.34 |
References | Authors | |
19 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gema Bello Orgaz | 1 | 116 | 10.36 |
| Julio C. Hernandez-Castro | 2 | 298 | 26.88 |
| David Camacho | 3 | 331 | 43.45 |