P-score: a reputation bibliographic index that complements citation counts

Scientometrics - The notions of reputation and popularity in academia are critical for taking decisions on research grants, faculty position tenure, and research excellence awards. These notions...     

Practical perfect hashing in nearly optimal space

A hash function is a mapping from a key universe U   to a range of integers, i.e., h:U?{0,1,…,m−1}$h:U?\{\mathrm{0,1},\dots ,m-1\}$, where m is the range's size. A perfect hash function   for some set S⊆U$S\subseteq U$ is a hash function that is one-to-one on S  , where m≥|S|$m\ge \left|S\right|$. A minimal perfect hash function   for some set S⊆U$S\subseteq U$ is a perfect hash function with a range of minimum size, i.e., m=|S|$m=\left|S\right|$. This paper presents a construction for (minimal) perfect hash functions that combines theoretical analysis, practical performance, expected linear construction time and nearly optimal space consumption for the data structure. For n keys and m=n   the space consumption ranges from 2.62n+o(n)$2.62n+o(n)$ to 3.3n+o(n)$3.3n+o(n)$ bits, and for m=1.23n$m=1.23n$ it ranges from 1.95n+o(n)$1.95n+o(n)$ to 2.7n+o(n)$2.7n+o(n)$ bits. This is within a small constant factor from the theoretical lower bounds of 1.44n$1.44n$ bits for m=n   and 0.89n$0.89n$ bits for m=1.23n$m=1.23n$. We combine several theoretical results into a practical solution that has turned perfect hashing into a very compact data structure to solve the membership problem when the key set S is static and known in advance. By taking into account the memory hierarchy we can construct (minimal) perfect hash functions for over a billion keys in 46 min using a commodity PC. An open source implementation of the algorithms is available at http://cmph.sf.net under the GNU Lesser General Public License (LGPL).     

Modeling the web as a hypergraph to compute page reputation

In this work we propose a model to represent the web as a directed hypergraph (instead of a graph), where links connect pairs of disjointed sets of pages. The web hypergraph is derived from the web graph by dividing the set of pages into non-overlapping blocks and using the links between pages of distinct blocks to create hyperarcs. A hyperarc connects a block of pages to a single page, in order to provide more reliable information for link analysis. We use the hypergraph model to create the hypergraph versions of the Pagerank and Indegree algorithms, referred to as HyperPagerank and HyperIndegree, respectively. The hypergraph is derived from the web graph by grouping pages by two different partition criteria: grouping together the pages that belong to the same web host or to the same web domain. We compared the original page-based algorithms with the host-based and domain-based versions of the algorithms, considering a combination of the page reputation, the textual content of the pages and the anchor text. Experimental results using three distinct web collections show that the HyperPagerank and HyperIndegree algorithms may yield better results than the original graph versions of the Pagerank and Indegree algorithms. We also show that the hypergraph versions of the algorithms were slightly less affected by noise links and spamming.     

Assessing the quality of scientific conferences based on bibliographic citations

Assessing the quality of scientific conferences is an important and useful service that can be provided by digital libraries and similar systems. This is specially true for fields such as Computer Science and Electric Engineering, where conference publications are crucial. However, the majority of the existing quality metrics, particularly those relying on bibliographic citations, has been proposed for measuring the quality of journals. In this article we conduct a study about the relative performance of existing journal metrics in assessing the quality of scientific conferences. More importantly, departing from a deep analysis of the deficiencies of these metrics, we propose a new set of quality metrics especially designed to capture intrinsic and important aspects related to conferences, such as longevity, popularity, prestige, and periodicity. To demonstrate the effectiveness of the proposed metrics, we have conducted two sets of experiments that contrast their results against a “gold standard” produced by a large group of specialists. Our metrics obtained gains of more than 12% when compared to the most consistent journal quality metric and up to 58% when compared to standard metrics such as Thomson’s Impact Factor.