Artificial Intelligence Review

最新影響指數 - 實時趨勢預測 & 期刊影響力排名

Impact factor is commonly used to evaluate the relative importance of a journal within its field and to measure the frequency with which the “average article” in a journal has been cited in a particular time period. Journal which publishes more review articles will get highest IFs. Journals with higher IFs believed to be more important than those with lower ones. According to Eugene Garfield “impact simply reflects the ability of the journals and editors to attract the best paper available.” Journal which publishes more review articles will get maximum IFs. The Journal Impact of an academic journal is a scientometric Metric that reflects the yearly average number of citations that recent articles published in a given journal received. It is frequently used as a Metric for the relative importance of a journal within its field; journals with higher Journal Impact are often deemed to be more important than those with lower ones. The Artificial Intelligence Review Journal Impact IF measures the average number of citations received in a particular year (2020) by papers published in the Artificial Intelligence Review during the two preceding years (2018-2019). Note that 2020 Journal Impact are reported in 2021; they cannot be calculated until all of the 2020 publications have been processed by the indexing agency. In addition to the 2-year Journal Impact, the 3-year Journal Impact can provide further insights and factors into the impact of Artificial Intelligence Review.

影響指數通常用於評估期刊在其領域內的相對重要性，以及衡量期刊在特定時間段內引用“平均文章”的頻率。發表更多評論文章的期刊將獲得最高的IF。 IF較高的期刊被認為比IF較低的期刊更重要。根據尤金·加菲爾德（Eugene Garfield）的說法，“影響只是反映期刊和編輯吸引最佳論文的能力。”發表更多評論文章的期刊將獲得最大的IF。