Google Scholar Metrics h5-index correlated with Impact Factor

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{ONeill:2012:TinyTOCSGSMhCwIF,

• author = "Michael O'Neill",
• title = "{Google Scholar} Metrics h5-index correlated with Impact Factor",
• journal = "Tiny Transactions on Computer Science",
• year = "2012",
• volume = "1",
• keywords = "genetic algorithms, genetic programming",
• URL = "http://tinytocs.org/vol1/",
• URL = "http://tinytocs.org/vol1/papers/tinytocs-v1-oneill.pdf",
• size = "1 page",
• abstract = "A number of rankings of Computer Science Conferences and Journals exist (e.g., CORE), however issues exist with these rankings, such as they are ageing rapidly, they are not actively updated, and there are differences in their methodologies and resulting rankings making them difficult to compare. A recent addition to the resources available to researchers evaluating the impact of their publications is Google Scholar Metrics. With this tool we can probe the impact of different publication venues (Conferences and Journals) according to citations using their five year h-index (h5-index) and five year h-median (h5-median). We present an analysis of different publication venues across the related fields of Artificial Intelligence, Machine Learning and Natural Computing amongst others, based upon Google Scholar Metrics and journal impact factors. A positive correlation is found between the h5-index (2007-2011) and impact factors (2010), and an overall ranking of the different venues finds that a number of top conferences in these fields have h5-index values equivalent, and in some cases superior to, the fields leading journals. Based on our analysis it is clear that publication in the top conference venues is of great importance in these fields, having similar impact to publication in journals. In times of multi-disciplinary research conveying this message (i.e., the relative importance of conference publication) to colleagues in other disciplines can be a challenge, and hopefully studies such as this will help to convey this message.",
• notes = "abstract approx 100 times size of text cites \cite{UCD-CSI-2012-02}",

}

Genetic Programming entries for Michael O'Neill

Citations