Yannis Manolopoulos

Yannis Manolopoulos
Open University of Cyprus · Faculty of Pure and Applied Sciences

Ph.D.

About

565
Publications
81,343
Reads
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11,930
Citations
Introduction
Skills and Expertise
Additional affiliations
September 1994 - present
Aristotle University of Thessaloniki
Position
  • Professor

Publications

Publications (565)
Article
Collective intelligence and Knowledge Exploration (CI and KE) have been adopted to solve many problems. They are particularly used by companies as a support for innovation to efficiently obtain usable results. CI is usually defined as a group ability to perform consistently well across a wide variety of tasks, and it has to be combined with KD to e...
Article
Combining multiple ranked lists of items, called voters, into a single consensus list is a popular problem with significant implications in numerous areas, including Bioinformatics, recommendation systems, metasearch engines, etc. Multiple recent solutions introduced supervised and unsupervised techniques that try to model the ordering of the list...
Article
The quality of the education provided and the research impact produced by universities is continuously evaluated at national and international level. This phenomenon is not new. However, nowadays education is not only considered as a social value and right/privilege, but also as a big economic sector, which addresses to large portions of population...
Chapter
Recommender systems in news industry use the time dimension to reveal users’ preferences over time, but they miss to exploit adequately the information encapsulated inside user sessions. Here, we combine intra- with inter-session item transition probabilities to reveal the short- and long-term intentions of individuals along with the public prefere...
Chapter
Publication and impact measures for individual scientists are used worldwide for various purposes such as funding, promotion, and consequently, the development of such indicators comprises a fertile research area. In this article,we propose two simple citation-based indicators, a dimensionless citation currency ratio (CCR) and a size-dependent cita...
Article
Full-text available
The rapid growth of users’ involvement in Location-Based Social Networks has led to the expeditious growth of the data on a global scale. The need of accessing and retrieving relevant information close to users’ preferences is an open problem which continuously raises new challenges for recommendation systems. The exploitation of points-of-interest...
Article
Recommender systems aim to provide users with recommendations of quality. New evaluation metrics such as diversity, have taken an increasing interest in a wide spectrum of applications, including the ecommerce, due to their ability to improve online revenues. High recommendation diversity allows a higher chance to satisfy the users’ needs. However,...
Article
Full-text available
In this work, we study the performance of state-of-the-art access methods to efficiently store and retrieve trajectories in spatial networks. First, we study how efficiently such methods can manage trajectory data to support indexing for data demanding applications where trajectory retrieval must be fast. At the same time, trajectory insertions, de...
Book
This book provides its readers with an introduction to interesting prediction and science dynamics problems in the field of Science of Science. Prediction focuses on the forecasting of future performance (or impact) of an entity, either a research article or a scientist, and also the prediction of future links in collaboration networks or identifyi...
Chapter
Skyline queries have earned a lot of attention due to their very wide application base in various domains such as multi-preference analysis and decision making. To better cater to application requirements, a number of research teams have put forward proposals for an extension of the definition of skyline on the basis of variants of the dominance re...
Chapter
This chapter presents the top-k dominating query with examples and several algorithms and solutions that have been proposed for efficient query processing. Top-k dominating queries have been studied by different perspectives, such as in indexed and non-indexed multi-dimensional data using efficient exact computation algorithms, in uncertain data us...
Chapter
In this chapter, we present various applications that are based on the dominance concept. There is actually a wide variety of applications that need dominance-based query processing facilities as fundamental building blocks in order to perform more complex operations. Some fields of applications include broad areas like Multi-Criteria Decision Maki...
Chapter
This chapter focuses on skyline query processing algorithms. First, we discuss algorithms that return the skyline of a set of points P that can fit in main memory. Next, we present techniques that are based on secondary memory. We cover both index-free and index-based query processing algorithms and we discuss about their advantages and disadvantag...
Article
Full-text available
Efficient query processing in spatial databases is of vital importance for numerous modern applications. In most cases, such processing is accomplished by taking advantage of spatial indexes. The xBR+-tree is an index for point data which has been shown to outperform indexes belonging to the R-tree family. On the other hand, Solid-State Drives (SSD...
Chapter
Full-text available
University rankings comprise a significant tool in making decisions in our modern educational process. In this paper, we propose a novel university ranking method based on the skyline operator, which is used on multi-dimensional objects to extract the non-dominated (i.e.“prevailing") ones. Our method is characterized by several advantages, such as:...
Article
Full-text available
Indexes are special purpose data structures, designed to facilitate and speed up the access to the contents of a file. Indexing has been actively and extensively investigated in DBMSes equipped with hard disk drives (HDDs). In the recent years, solid-state drives (SSDs), based on NAND flash technology, started replacing magnetic disks due to their...
Book
The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for r...
Book
This book constitutes the proceedings of the 23rd International Conference on Discovery Science, DS 2020, which took place during October 19-21, 2020. The conference was planned to take place in Thessaloniki, Greece, but had to change to an online format due to the COVID-19 pandemic. The 26 full and 19 short papers presented in this volume were car...
Article
Full-text available
Large image collections are being used in many modern applications. In this paper, we aim at capturing the intrinsic dissimilarities of image descriptors in large image collections, i.e., to detect dissimilar (or else diverse) images without defining an explicit similarity or distance measure. Towards this goal, we adopt skyline processing techniqu...
Article
Full-text available
Due to the ubiquitous use of spatial data applications and the large amounts of such data these applications use, the processing of large scale distance joins in distributed systems is becoming increasingly popular. Distance Join Queries (DJQs) are important and frequently used operations in numerous applications, including data mining, multimedia...
Chapter
Hidden graphs are flexible abstractions that are composed of a set of known vertices (nodes), whereas the set of edges are not known in advance. To uncover the set of edges, multiple edge probing queries must be executed by evaluating a function f(u, v) that returns either true or false, if nodes u and v are connected or not respectively. Evidently...
Conference Paper
Virtual assistants, also known as intelligent conversational systems such as Google's Virtual Assistant and Apple's Siri, interact with human-like responses to users' queries and finish specific tasks. Meanwhile, existing recommendation technologies model users' evolving, diverse and multi-aspect preferences to generate recommendations in various d...
Preprint
Full-text available
Hidden graphs are flexible abstractions that are composed of a set of known vertices (nodes), whereas the set of edges are not known in advance. To uncover the set of edges, multiple edge probing queries must be executed by evaluating a function $f(u,v)$ that returns either true or false, if nodes $u$ and $v$ are connected or not respectively. Evid...
Article
Spatial indexes are important in spatial databases for efficient execution of queries involving spatial constraints. The \(\hbox {xBR}^{+}\hbox {-tree}\) is a balanced, disk-resident, Quadtree-based index for point data, which is very efficient for processing spatial queries. Bulk-loading refers to the process of creating an index from scratch as a...
Preprint
The rapid growth of users' involvement in Location-Based Social Networks (LBSNs) has led to the expeditious growth of the data on a global scale. The need of accessing and retrieving relevant information close to users' preferences is an open problem which continuously raises new challenges for recommendation systems. The exploitation of Points-of-...
Article
Full-text available
Nowadays university rankings are ubiquitous commodities; a plethora of them is published every year by private enterprises, state authorities and universities. University rankings are very popular to governments, journalists, university administrations and families as well. At the same time, they are heavily criticized as being very subjective and...
Article
With the rising interest in predicting the scientific output, various efforts have been made to predict a scientist's h-index or the citation trajectory of a publication. In this work, we employ a dynamic categorization for scientists to ensure at each stage of their careers a comparison amongst their peers and combine this grouping with predictive...
Conference Paper
During the past two decades the availability of scholarly data repositories such as Google Scholar, Elsevier Scopus offered tremendous opportunities to the field of scientometrics to analyze the dynamics of science and help design indicators to evaluate the scientific impact of scholars, journals and academic institutions. Thus, scientometrics tran...
Conference Paper
The range skyline query retrieves the dynamic skyline for every individual query point in a range by generalizing the point-based dynamic skyline query. Its wide-ranging applications enable users to submit their preferences within an interval of 'ideally sought' values across every dimension, instead of being limited to submit their preference in r...
Conference Paper
Full-text available
Despite the rich ecosystem of scientometric indicators that quantify an individual's scientific research output, these indicators either loose singificant information that resides in the citation curve of a scien-tist's work or they can not capture the multi-dimensional aspects of the scientist's performance. Based on these observations, we outline...
Conference Paper
The reverse k-nearest neighbours search is a fundamental primitive in multi-dimensional (i.e. multi-attribute) databases with applications in location-based services, online recommendations, statistical classification, pat-tern recognition, graph algorithms, computer games development, and so on. Despite the relevance and popularity of the query, n...
Article
Various scientometric indices have been proposed in an attempt to express the quantitative and qualitative characteristics of scientific output. However, fully capturing the performance and impact of a scientific entity (author, journal, institution, conference, etc.) still remains an open research issue, as each proposed index focuses only on part...
Article
Full-text available
Efficient processing of Distance-Based Join Queries (DBJQs) in spatial databases is of paramount importance in many application domains. The most representative and known DBJQs are the K Closest Pairs Query (KCPQ) and the ε Distance Join Query (εDJQ). These types of join queries are characterized by a number of desired pairs (K) or a distance thres...
Article
Full-text available
Recommender systems in location-based social networks (LBSNs), such as Facebook Places and Foursquare, have focused on recommending friends or locations to registered users by combining information derived from explicit (i.e. friendship network) and implicit (i.e. user-item rating network, user-location network, etc.) sub-networks. However, previou...
Book
This three-volume set LNCS 11139-11141 constitutes the refereed proceedings of the 27th International Conference on Artificial Neural Networks, ICANN 2018, held in Rhodes, Greece, in October 2018. The papers presented in these volumes was carefully reviewed and selected from total of 360 submissions. They are related to the following thematic topic...
Book
This book constitutes the refereed proceedings of the 19th International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2017, held in Moscow, Russia, in October 2017. The 16 revised full papers presented together with three invited papers were carefully reviewed and selected from 75 submissions. The papers are or...
Conference Paper
Spatial access methods have been extensively studied in the literature, during last decades. Access methods were designed for efficient processing of demanding queries and extensive comparisons between such methods have been presented. However, choosing the best values for the parameters that affect the performance of a spatial access method when s...
Conference Paper
In this paper we try to detect dissimilar images in image databases without defining a similarity ranking function by capturing the intrinsic dissimilarities of image descriptor vectors. To this end, we apply the skyline operation using their multi-dimensional descriptor vectors. We implemented a number of skyline methods, combined with four hashin...
Conference Paper
Full-text available
Various scientometric indices have been proposed in an attempt to express the quantitative and qualitative characteristics of scientific output. In this paper, we revisit several scientometrics indicators and apply the Rainbow Ranking method [1] [2] to categorize the academic personnel of the Departments of Informatics (Computer Science and Enginee...
Conference Paper
Various efforts have been made to quantify scientific impact and identify the mechanisms that influence its future evolution. The first step is the identification of what constitutes scholarly impact and how it is measured. In this direction, various approaches focus on future citation count or h-index prediction at author or publication level, on...
Conference Paper
Bulk insertion refers to the process of updating an existing index by inserting a large batch of new data, treating the items of this batch as a whole and not by inserting these items one-by-one. Bulk insertion is related to bulk loading, which refers to the process of creating a non-existing index from scratch, when the dataset to be indexed is av...
Article
Full-text available
This article presents an anatomy of PhD programmes in Hellenic universities' departments of computer science/engineering from the perspective of research productivity and impact. The study aims at showing the dynamics of research conducted in computer science/engineering departments, and after recognizing weaknesses, to motivate the stakeholders to...
Article
Processing of spatial queries has been studied extensively in the literature. In most cases, it is accomplished by indexing spatial data using spatial access methods. Spatial indexes, such as those based on the Quadtree, are important in spatial databases for efficient execution of queries involving spatial constraints and objects. In this paper, w...
Article
A major part of the interface to a database is made up of the queries that can be addressed to this database and answered (processed) in an efficient way, contributing to the quality of the developed software. Efficiently processed spatial queries constitute a fundamental part of the interface to spatial databases due to the wide area of applicatio...
Conference Paper
In this paper we provide an introduction to the field of Bibliometrics. In particular, first we briefly describe its beginning and its evolution; we mention the main research fora as well. Further we categorize metrics according to their entity scope: metrics for journals, conferences and authors. Several rankings have appeared based on such metric...
Conference Paper
The skyline query aims to filter out a set of eligible points on the basis of a set of evaluation criteria and out of a potentially large dataset of points. The computation of this decision support problem has been studied across a wide range of environments and of types of data. A field of research that has remained unexplored in the context of th...
Article
Treating brain as a complex system is currently among the most popular approaches that are used to understand its function and explain encephalopathies. The networked epileptic brain has already been studied through various neuroimaging modalities based on estimates of functional connectivity. Here, we suggest that additional insights to epileptoge...
Article
Assorted bibliometric indices have been proposed leading to ambiguity in choosing the appropriate metric for evaluation. On the other hand, attempts to fit universal distribution patterns to scientific output have not converged to unified conclusions. To this end, we introduce the concept of fractal dimension to further examine the citation curve o...
Article
Location-Based Social Networks (LBSNs) allow users to post ratings and reviews and to notify friends of these posts. Several models have been proposed for Point-of-Interest (POI) recommendation that use explicit (i.e. ratings, comments) or implicit (i.e. statistical scores, views, and user influence) information. However the models so far fail to c...
Conference Paper
Automated online profiling consists of the accurate identification and linking of multiple online identities across heterogeneous online social networks that correspond to the same entity in the physical world. The paper proposes a hybrid profile correlation model which relies on a diversity of techniques from different application domains, such as...
Article
Recommender systems elicit the interests and preferences of individuals and make recommendations accordingly, a main challenge for expert and intelligent systems. An essential problem in recommender systems is to learn users’ preference dynamics, that is, the constant evolution of the explicit or the implicit information, which is diversified throu...
Book
This book constitutes the refereed proceedings of the 28th International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2016, held in Ershovo, Moscow, Russia, in October 2016. The 16 revised full papers presented together with one invited talk and two keynote papers were carefully reviewed and selected from 57 su...
Book
The book offers a timely snapshot of neural network technologies as a significant component of big data analytics platforms. It promotes new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms); implementations on different compu...
Book
This book constitutes the proceedings of the 21st International Conference on Theory and Practice of Digital Libraries, TPDL 2017, held in Thessaloniki, Greece, in September 2017. The 39 full papers, 11 short papers, and 10 poster papers presented in this volume were carefully reviewed and selected from 106 submissions. In addition the book contain...
Article
Full-text available
Recent Big Data research typically emphasizes on the need to address the challenges stemming from the volume, velocity, variety and veracity aspects. However, another cross-cutting property of Big Data is volatility. In database technology, volatility is addressed with the help of adaptive query processing (AQP), which has become the dominant parad...
Article
Full-text available
Efficient and effective processing of the distance-based join query (DJQ) is of great importance in spatial databases due to the wide area of applications that may address such queries (mapping, urban planning, transportation planning, resource management, etc.). The most representative and studied DJQs are the K Closest Pairs Query (KCPQ) and εDis...
Conference Paper
Spatial indexes are important in spatial databases for efficient execution of queries involving spatial constraints. The xBR\(^+\)-tree is a balanced disk-resident quadtree-based index structure for point data, which is very efficient for processing such queries. Bulk-loading refers to the process of creating an index from scratch as a whole, when...
Conference Paper
We compare three algorithms for skyline processing on streams of multidimensional data with centralized processing, namely, the LookOut, Lazy and Eager methods, with different dataset types and dimensionalities, data cardinalities and sliding window sizes. Experimental results for time performance and memory consumption are presented. In addition,...
Conference Paper
The East-European Conference in Advances in Data Bases & Information Systems (ADBIS) spans 20 years of life. Here, by using simple statistic measures and bibliographic analysis, we illustrate basic characteristics and features of ADBIS, i.e. the venues, persons and countries involved. Also, its international character, its competitiveness and its s...
Conference Paper
Given two datasets P and Q, the K Closest Pair Query (KCPQ) finds the K closest pairs of objects from \(P \times Q\). It is an operation widely adopted by many spatial and GIS applications. As a combination of the K Nearest Neighbor (KNN) and the spatial join queries, KCPQ is an expensive operation. Given the increasing volume of spatial data, it i...