Researcher profile

Yannis Manolopoulos

Yannis Manolopoulos contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate

Trust snapshot

Quick read

Trust 15 - UnverifiedVerification L1Unclaimed author
3works
0followers
3topics
4close collaborators

Actions

Decide how to stay connected

Follow researcher0

Identity and collaboration

How to connect with this researcher

Claiming links this public author record to a researcher profile and unlocks direct collaboration workflows.

Log in to claim

Direct collaboration

Open a focused conversation when the fit is right

Claim this author entity first to unlock direct invitations.

Research graph

See the researcher in context

Open full explorer

Inspect adjacent work, topics, institutions and collaborators without jumping out to a separate graph page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Published work

3 published item(s)

preprint2026arXiv

A contemporary science map through the lens of IEEE and ACM periodicals

ACM and IEEE are the two premier associations on computing and electrical/electronics engineering which publish and organize the great majority of periodicals and conferences, respectively, serving these disciplines. Science is a constantly evolving process, and these publication fora are expected to follow the trends. In this article, we focus on the periodicals published by the two associations and seek to detect and/or confirm any contemporary science trends as these are reflected to the periodical titles established recently. Our study is rather qualitative than quantitative, aiming at revealing patterns immediately comprehensible and validatable by the reader. Among the most notable patterns, we see a growing preference of both associations for the open access mode of publication; we also observe ACM's orientation toward AI-focused periodicals, and most importantly, a significant theme overlap among periodicals of the same association and this is valid for both ACM and IEEE.

preprint2013arXiv

Categorizing Influential Authors Using Penalty Areas

The concept of h-index has been proposed to easily assess a researcher's performance with a single two-dimensional number. However, by using only this single number, we lose significant information about the distribution of the number of citations per article of an author's publication list. Two authors with the same h-index may have totally different distributions of the number of citations per article. One may have a very long "tail" in the citation curve, i.e. he may have published a great number of articles, which did not receive relatively many citations. Another researcher may have a short tail, i.e. almost all his publications got a relatively large number of citations. In this article, we study an author's citation curve and we define some areas appearing in this curve. These areas are used to further evaluate authors' research performance from quantitative and qualitative point of view. We call these areas as "penalty" ones, since the greater they are, the more an author's performance is penalized. Moreover, we use these areas to establish new metrics aiming at categorizing researchers in two distinct categories: "influential" ones vs. "mass producers".

preprint2012arXiv

ART : Sub-Logarithmic Decentralized Range Query Processing with Probabilistic Guarantees

We focus on range query processing on large-scale, typically distributed infrastructures, such as clouds of thousands of nodes of shared-datacenters, of p2p distributed overlays, etc. In such distributed environments, efficient range query processing is the key for managing the distributed data sets per se, and for monitoring the infrastructure's resources. We wish to develop an architecture that can support range queries in such large-scale decentralized environments and can scale in terms of the number of nodes as well as in terms of the data items stored. Of course, in the last few years there have been a number of solutions (mostly from researchers in the p2p domain) for designing such large-scale systems. However, these are inadequate for our purposes, since at the envisaged scales the classic logarithmic complexity (for point queries) is still too expensive while for range queries it is even more disappointing. In this paper we go one step further and achieve a sub-logarithmic complexity. We contribute the ART, which outperforms the most popular decentralized structures, including Chord (and some of its successors), BATON (and its successor) and Skip-Graphs. We contribute theoretical analysis, backed up by detailed experimental results, showing that the communication cost of query and update operations is $O(\log_{b}^2 \log N)$ hops, where the base $b$ is a double-exponentially power of two and $N$ is the total number of nodes. Moreover, ART is a fully dynamic and fault-tolerant structure, which supports the join/leave node operations in $O(\log \log N)$ expected w.h.p number of hops. Our experimental performance studies include a detailed performance comparison which showcases the improved performance, scalability, and robustness of ART.