P
Per Ahlgren
Researcher at Uppsala University
Publications - 61
Citations - 1463
Per Ahlgren is an academic researcher from Uppsala University. The author has contributed to research in topics: Relevance (information retrieval) & Citation impact. The author has an hindex of 15, co-authored 57 publications receiving 1262 citations. Previous affiliations of Per Ahlgren include Umeå University & Chinese Academy of Sciences.
Papers
More filters
Journal ArticleDOI
Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient
TL;DR: It is concluded that Pearson's r is probably not an optimal choice of a similarity measure in ACA and further empirical research is needed to show if, and in that case to what extent, the use of similarity measures in ACA that fulfill these requirements would lead to objectively better results In full-scale studies.
Journal ArticleDOI
Document-document similarity approaches and science mapping : experimental comparison of five approaches
Per Ahlgren,Cristian Colliander +1 more
TL;DR: It is shown that it is possible to achieve a very good approximation of the classification by means of automatic grouping of articles, and how well the approaches agree with a ground truth subject classification of the test documents is investigated.
Journal ArticleDOI
Author cocitation analysis and Pearson's r
Journal ArticleDOI
The effects and their stability of field normalization baseline on relative performance with respect to citation impact : a case study of 20 natural science departments
Cristian Colliander,Per Ahlgren +1 more
TL;DR: The results show that the choice of normalization baseline matters, and that people without access to subject category data can perform reasonable normalized citation impact studies by combining normalization against journal withnormalization against Essential Science Indicators field.
Journal ArticleDOI
Granularity of algorithmically constructed publication-level classifications of research publications : Identification of topics
TL;DR: The results of two case studies show that the topics of the cases are closely associated with different classes of the identified ACPLC, and that these classes tend to treat only one topic, and the proposed methodology is suitable to determine the topic granularity level of an ACP LC.