  This paper explores a dual score system that simultaneously evaluates the
relative importance of researchers and their works. It is a modification of the
CITEX algorithm recently described in Pal and Ruj (2015). Using available
publication data for $m$ author keywords (as a proxy for researchers) and $n$
papers it is possible to construct a $m \times n$ author-paper feature matrix.
This is further combined with citation data to construct a HITS-like algorithm
that iteratively satisfies two criteria: first, \emph{a good author is cited by
good authors}, and second, \emph{a good paper is cited by good authors}.
Following Pal and Ruj, the resulting algorithm produces an author eigenscore
and a paper eigenscore. The algorithm is tested on 213,530 citable publications
listed under Thomson ISI's "\emph{Information Science \& Library Science}" JCR
category from 1980--2012.
