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187 results on '"Skiadopoulos, Spiros"'

1. A Crawler Architecture for Harvesting the Clear, Social, and Dark Web for IoT-Related Cyber-Threat Intelligence

Author

Koloveas, Paris, Chantzios, Thanasis, Tryfonopoulos, Christos, and Skiadopoulos, Spiros

Subjects
Computer Science - Cryptography and Security, Computer Science - Machine Learning
Abstract

The clear, social, and dark web have lately been identified as rich sources of valuable cyber-security information that -given the appropriate tools and methods-may be identified, crawled and subsequently leveraged to actionable cyber-threat intelligence. In this work, we focus on the information gathering task, and present a novel crawling architecture for transparently harvesting data from security websites in the clear web, security forums in the social web, and hacker forums/marketplaces in the dark web. The proposed architecture adopts a two-phase approach to data harvesting. Initially a machine learning-based crawler is used to direct the harvesting towards websites of interest, while in the second phase state-of-the-art statistical language modelling techniques are used to represent the harvested information in a latent low-dimensional feature space and rank it based on its potential relevance to the task at hand. The proposed architecture is realised using exclusively open-source tools, and a preliminary evaluation with crowdsourced results demonstrates its effectiveness., Comment: 6 pages, 2 figures

Published
2021
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2. Local Similarity Search on Geolocated Time Series Using Hybrid Indexing

Author

Chatzigeorgakidis, Georgios, Skoutas, Dimitrios, Patroumpas, Kostas, Palpanas, Themis, Athanasiou, Spiros, and Skiadopoulos, Spiros

Subjects
Computer Science - Databases, 68P05, E.1
Abstract

Geolocated time series, i.e., time series associated with certain locations, abound in many modern applications. In this paper, we consider hybrid queries for retrieving geolocated time series based on filters that combine spatial distance and time series similarity. For the latter, unlike existing work, we allow filtering based on local similarity, which is computed based on subsequences rather than the entire length of each series, thus allowing the discovery of more fine-grained trends and patterns. To efficiently support such queries, we first leverage the state-of-the-art BTSR-tree index, which utilizes bounds over both the locations and the shapes of time series to prune the search space. Moreover, we propose optimizations that check at specific timestamps to identify candidate time series that may exceed the required local similarity threshold. To further increase pruning power, we introduce the SBTSR-tree index, an extension to BTSR-tree, which additionally segments the time series temporally, allowing the construction of tighter bounds. Our experimental results on several real-world datasets demonstrate that SBTSR-tree can provide answers much faster for all examined query types. This paper has been published in the 27th International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2019).

Published
2021

3. Local Pair and Bundle Discovery over Co-Evolving Time Series

Author

Chatzigeorgakidis, Georgios, Skoutas, Dimitrios, Patroumpas, Kostas, Palpanas, Themis, Athanasiou, Spiros, and Skiadopoulos, Spiros

Subjects
Computer Science - Data Structures and Algorithms, 68P05, E.1
Abstract

Time series exploration and mining has many applications across several industrial and scientific domains. In this paper, we consider the problem of detecting locally similar pairs and groups, called bundles, over co-evolving time series. These are pairs or groups of subsequences whose values do not differ by more than {\epsilon} for at least delta consecutive timestamps, thus indicating common local patterns and trends. We first present a baseline algorithm that performs a sweep line scan across all timestamps to identify matches. Then, we propose a filter-verification technique that only examines candidate matches at judiciously chosen checkpoints across time. Specifically, we introduce two block scanning algorithms for discovering local pairs and bundles respectively, which leverage the potential of checkpoints to aggressively prune the search space. We experimentally evaluate our methods against real-world and synthetic datasets, demonstrating a speed-up in execution time by an order of magnitude over the baseline. This paper has been published in the 16th International Symposium on Spatial and Temporal Databases (SSTD19)., Comment: 16 pages, 16 figures

Published
2021

4. Twin Subsequence Search in Time Series

Author

Chatzigeorgakidis, Georgios, Skoutas, Dimitrios, Patroumpas, Kostas, Palpanas, Themis, Athanasiou, Spiros, and Skiadopoulos, Spiros

Subjects
Computer Science - Data Structures and Algorithms, 68P05, E.1
Abstract

We address the problem of subsequence search in time series using Chebyshev distance, to which we refer as twin subsequence search. We first show how existing time series indices can be extended to perform twin subsequence search. Then, we introduce TS-Index, a novel index tailored to this problem. Our experimental evaluation compares these approaches against real time series datasets, and demonstrates that TS-Index can retrieve twin subsequences much faster under various query conditions. This paper has been published in the 24th International Conference on Extending Database Technology (EDBT 2021)., Comment: 6 pages, 8 figures

Published
2021

6. Adaptive Content-Aware Influence Maximization via Online Learning to Rank.

Author

Theocharidis, Konstantinos, Karras, Panagiotis, Terrovitis, Manolis, Skiadopoulos, Spiros, and Lauw, Hady W.

Subjects
ONLINE education, SOCIAL networks, CLASSROOM environment
Abstract

How can we adapt the composition of a post over a series of rounds to make it more appealing in a social network? Techniques that progressively learn how to make a fixed post more influential over rounds have been studied in the context of the Influence Maximization (IM) problem, which seeks a set of seed users that maximize a post's influence. However, there is no work on progressively learning how a post's features affect its influence. In this article, we propose and study the problem of Adaptive Content-Aware Influence Maximization (ACAIM), which calls to find k features to form a post in each round so as to maximize the cumulative influence of those posts over all rounds. We solve ACAIM by applying, for the first time, an Online Learning to Rank (OLR) framework for IM purposes. We introduce the CATRID propagation model, which expresses how posts disseminate in a social network using click probabilities and post visibility criteria and develop a simulator that runs CATRID via a training-testing scheme based on real posts of the VK social network, so as to realistically represent the learning environment. We deploy three learners that solve ACAIM in an online (real-time) manner. We experimentally prove the practical suitability of our solutions via exhaustive experiments on multiple brands (operating as different case studies) and several VK datasets; the best learner is evaluated on 45 separate case studies yielding convincing results. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Link Prediction in Bibliographic Networks

Author

Chronis, Pantelis, Skoutas, Dimitrios, Athanasiou, Spiros, Skiadopoulos, Spiros, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Bellatreche, Ladjel, editor, Bieliková, Mária, editor, Boussaïd, Omar, editor, Catania, Barbara, editor, Darmont, Jérôme, editor, Demidova, Elena, editor, Duchateau, Fabien, editor, Hall, Mark, editor, Merčun, Tanja, editor, Novikov, Boris, editor, Papatheodorou, Christos, editor, Risse, Thomas, editor, Romero, Oscar, editor, Sautot, Lucile, editor, Talens, Guilaine, editor, Wrembel, Robert, editor, and Žumer, Maja, editor

Published
2020
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8. A Study on the Readability of Scientific Publications

Author

Vergoulis, Thanasis, Kanellos, Ilias, Tzerefos, Anargiros, Chatzopoulos, Serafeim, Dalamagas, Theodore, Skiadopoulos, Spiros, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Doucet, Antoine, editor, Isaac, Antoine, editor, Golub, Koraljka, editor, Aalberg, Trond, editor, and Jatowt, Adam, editor

Published
2019
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9. Full-text Support for Publish/Subscribe Ontology Systems

Author

Zervakis, Lefteris, Tryfonopoulos, Christos, Papadakis-Pesaresi, Antonios, Koubarakis, Manolis, and Skiadopoulos, Spiros

Subjects
Computer Science - Information Retrieval, Computer Science - Databases
Abstract

We envision a publish/subscribe ontology system that is able to index millions of user subscriptions and filter them against ontology data that arrive in a streaming fashion. In this work, we propose a SPARQL extension appropriate for a publish/subscribe setting; our extension builds on the natural semantic graph matching of the language and supports the creation of full-text subscriptions. Subsequently, we propose a main-memory subscription indexing algorithm which performs both semantic and full-text matching at low complexity and minimal filtering time. Thus, when ontology data are published matching subscriptions are identified and notifications are forwarded to users., Comment: ESWC 2012 Demo

Published
2013

11. Unsupervised Disaggregation of Low Granularity Resource Consumption Time Series

Author

Chronis, Pantelis, Giannopoulos, Giorgos, Athanasiou, Spiros, Skiadopoulos, Spiros, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Phung, Dinh, editor, Tseng, Vincent S., editor, Webb, Geoffrey I., editor, Ho, Bao, editor, Ganji, Mohadeseh, editor, and Rashidi, Lida, editor

Published
2018
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13. Privacy Preservation by Disassociation

Author

Terrovitis, Manolis, Liagouris, John, Mamoulis, Nikos, and Skiadopoulos, Spiros

Subjects
Computer Science - Databases
Abstract

In this work, we focus on protection against identity disclosure in the publication of sparse multidimensional data. Existing multidimensional anonymization techniquesa) protect the privacy of users either by altering the set of quasi-identifiers of the original data (e.g., by generalization or suppression) or by adding noise (e.g., using differential privacy) and/or (b) assume a clear distinction between sensitive and non-sensitive information and sever the possible linkage. In many real world applications the above techniques are not applicable. For instance, consider web search query logs. Suppressing or generalizing anonymization methods would remove the most valuable information in the dataset: the original query terms. Additionally, web search query logs contain millions of query terms which cannot be categorized as sensitive or non-sensitive since a term may be sensitive for a user and non-sensitive for another. Motivated by this observation, we propose an anonymization technique termed disassociation that preserves the original terms but hides the fact that two or more different terms appear in the same record. We protect the users' privacy by disassociating record terms that participate in identifying combinations. This way the adversary cannot associate with high probability a record with a rare combination of terms. To the best of our knowledge, our proposal is the first to employ such a technique to provide protection against identity disclosure. We propose an anonymization algorithm based on our approach and evaluate its performance on real and synthetic datasets, comparing it against other state-of-the-art methods based on generalization and differential privacy., Comment: VLDB2012

Published
2012

14. ERA: Efficient Serial and Parallel Suffix Tree Construction for Very Long Strings

Author

Mansour, Essam, Allam, Amin, Skiadopoulos, Spiros, and Kalnis, Panos

Subjects
Computer Science - Databases
Abstract

The suffix tree is a data structure for indexing strings. It is used in a variety of applications such as bioinformatics, time series analysis, clustering, text editing and data compression. However, when the string and the resulting suffix tree are too large to fit into the main memory, most existing construction algorithms become very inefficient. This paper presents a disk-based suffix tree construction method, called Elastic Range (ERa), which works efficiently with very long strings that are much larger than the available memory. ERa partitions the tree construction process horizontally and vertically and minimizes I/Os by dynamically adjusting the horizontal partitions independently for each vertical partition, based on the evolving shape of the tree and the available memory. Where appropriate, ERa also groups vertical partitions together to amortize the I/O cost. We developed a serial version; a parallel version for shared-memory and shared-disk multi-core systems; and a parallel version for shared-nothing architectures. ERa indexes the entire human genome in 19 minutes on an ordinary desktop computer. For comparison, the fastest existing method needs 15 minutes using 1024 CPUs on an IBM BlueGene supercomputer., Comment: VLDB2012

Published
2011

18. Full-Text Support for Publish/Subscribe Ontology Systems

Author

Zervakis, Lefteris, Tryfonopoulos, Christos, Skiadopoulos, Spiros, Koubarakis, Manolis, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Sack, Harald, editor, Blomqvist, Eva, editor, d'Aquin, Mathieu, editor, Ghidini, Chiara, editor, Ponzetto, Simone Paolo, editor, and Lange, Christoph, editor

Published
2016
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23. Anonymizing Data with Relational and Transaction Attributes

Author

Poulis, Giorgos, Loukides, Grigorios, Gkoulalas-Divanis, Aris, Skiadopoulos, Spiros, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Blockeel, Hendrik, editor, Kersting, Kristian, editor, Nijssen, Siegfried, editor, and Železný, Filip, editor

Published
2013
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24. A Content Recommendation Policy for Gaining Subscribers

Author

Theocharidis, Konstantinos, Terrovitis, Manolis, Skiadopoulos, Spiros, and Karras, Panagiotis

Subjects
subscription gain, ranking, messaging, content recommendation
Abstract

How can we recommend content for a brand agent to use over a series of rounds so as to gain new subscribers to its social network page? The Influence Maximization (IM) problem seeks a set of∼k users, and its content-aware variants seek a set of∼k post features, that achieve, in both cases, an objective of expected influence in a social network. However, apart from raw influence, it is also relevant to study gain in subscribers, as long-term success rests on the subscribers of a brand page; classic IM may select∼k users from the subscriber set, and content-aware IM starts the post's propagation from that subscriber set. In this paper, we propose a novel content recommendation policy to a brand agent for Gaining Subscribers by Messaging (GSM) over many rounds. In each round, the brand agent messages a fixed number of social network users and invites them to visit the brand page aiming to gain their subscription, while its most recently published content consists of features that intensely attract the preferences of the invited users. To solve GSM, we find, in each round, which content features to publish and which users to notify aiming to maximize the cumulative subscription gain over all rounds. We deploy three GSM solvers, named \sR, \sSC, and \sSU, and we experimentally evaluate their performance based on VKontakte (VK) posts by considering different user sets and feature sets. Our experimental results show that \sSU provides the best solution, as it is significantly more efficient than \sSC with a minor loss of efficacy and clearly more efficacious than \sR with competitive efficiency.

Published
2022

26. Evaluating Reachability Queries over Path Collections

Author

Bouros, Panagiotis, Skiadopoulos, Spiros, Dalamagas, Theodore, Sacharidis, Dimitris, Sellis, Timos, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, and Winslett, Marianne, editor

Published
2009
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28. MobiHide: A Mobilea Peer-to-Peer System for Anonymous Location-Based Queries

Author

Ghinita, Gabriel, Kalnis, Panos, Skiadopoulos, Spiros, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Papadias, Dimitris, editor, Zhang, Donghui, editor, and Kollios, George, editor

Published
2007
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29. Blueprints and Measures for ETL Workflows

Author

Vassiliadis, Panos, Simitsis, Alkis, Terrovitis, Manolis, Skiadopoulos, Spiros, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Delcambre, Lois, editor, Kop, Christian, editor, Mayr, Heinrich C., editor, Mylopoulos, John, editor, and Pastor, Oscar, editor

Published
2005
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30. Graph-Based Modeling of ETL Activities with Multi-level Transformations and Updates

Author

Simitsis, Alkis, Vassiliadis, Panos, Terrovitis, Manolis, Skiadopoulos, Spiros, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Tjoa, A Min, editor, and Trujillo, Juan, editor

Published
2005
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32. Computing and Handling Cardinal Direction Information

Author

Skiadopoulos, Spiros, Giannoukos, Christos, Vassiliadis, Panos, Sellis, Timos, Koubarakis, Manolis, Goos, Gerhard, editor, Hartmanis, Juris, editor, van Leeuwen, Jan, editor, Bertino, Elisa, editor, Christodoulakis, Stavros, editor, Plexousakis, Dimitris, editor, Christophides, Vassilis, editor, Koubarakis, Manolis, editor, Böhm, Klemens, editor, and Ferrari, Elena, editor

Published
2004
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33. CPM: A Cube Presentation Model for OLAP

Author

Maniatis, Andreas, Vassiliadis, Panos, Skiadopoulos, Spiros, Vassiliou, Yannis, Goos, Gerhard, editor, Hartmanis, Juris, editor, van Leeuwen, Jan, editor, Kambayashi, Yahiko, editor, Mohania, Mukesh, editor, and Wöß, Wolfram, editor

Published
2003
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34. Chapter 5: Spatio-temporal Models and Languages: An Approach Based on Constraints

Author

Grumbach, Stéphane, Koubarakis, Manolis, Rigaux, Philippe, Scholl, Michel, Skiadopoulos, Spiros, Goos, Gerhard, editor, Hartmanis, Juris, editor, van Leeuwen, Jan, editor, Sellis, Timos K., editor, Koubarakis, Manolis, editor, Frank, Andrew, editor, Grumbach, Stéphane, editor, Güting, Ralf Hartmut, editor, Jensen, Christian, editor, Lorentzos, Nikos A., editor, Manolopoulos, Yannis, editor, Nardelli, Enrico, editor, Pernici, Barbara, editor, Theodoulidis, Babis, editor, Tryfona, Nectaria, editor, Schek, Hans-Jörg, editor, and Scholl, Michel O., editor

Published
2003
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35. On the Logical Modeling of ETL Processes

Author

Vassiliadis, Panos, Simitsis, Alkis, Skiadopoulos, Spiros, Goos, Gerhard, editor, Hartmanis, Juris, editor, van Leeuwen, Jan, editor, Pidduck, Anne Banks, editor, Ozsu, M. Tamer, editor, Mylopoulos, John, editor, and Woo, Carson C., editor

Published
2002
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37. Composing Cardinal Direction Relations

Author

Skiadopoulos, Spiros, Koubarakis, Manolis, Goos, G., editor, Hartmanis, J., editor, van Leeuwen, J., editor, Jensen, Christian S., editor, Schneider, Markus, editor, Seeger, Bernhard, editor, and Tsotras, Vassilis J., editor

Published
2001
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43. Efficient Range and kNN Twin Subsequence Search in Time Series

Author

Chatzigeorgakidis, Georgios, Skoutas, Dimitrios, Patroumpas, Kostas, Palpanas, Themis, Athanasiou, Spiros, and Skiadopoulos, Spiros

Abstract

Analyzing time series data is crucial for many applications. In particular, subsequence search refers to finding subsequences within an input time series $T$T that are similar to a query sequence $Q$Q. Existing subsequence search approaches typically employ Euclidean distance or Dynamic Time Warping as similarity measures and address range queries. In this paper, we focus on Chebyshev distance, which is the largest difference between each individual pair of points across the entire length of two compared subsequences. We call such similar pairs twins. We first show how existing time series indices can be extended to perform twin subsequence search. Then, we introduce TS-Index, a novel index tailored to the computation of twin subsequence search queries. Moreover, given that specifying a distance threshold is often not straightforward, we show how TS-Index can also be used to evaluate $k$kNN queries. Our extensive experimental evaluation compares these approaches using real time series datasets. The results demonstrate that TS-Index can retrieve twin subsequences faster than all other methods under various conditions.

Published
2023
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45. Storing and indexing spatial data in P2P systems

Author

Kantere, Verena, Skiadopoulos, Spiros, and Sellis, Timos

Subjects
Peer to peer computing -- Usage, Peer to peer computing -- Research, Geospatial data -- Analysis, Business, Computers, Electronics, Electronics and electrical industries
Abstract

The peer-to-peer (P2P) paradigm has become very popular for storing and sharing information in a totally decentralized manner. At first, research focused on P2P systems that host 1 D data. Nowadays, the need for P2P applications with multidimensional data has emerged, motivating research on P2P systems that manage such data. The majority of the proposed techniques are based either on the distribution of centralized indexes or on the reduction of multidimensional data to one dimension. Our goal is to create from scratch a technique that is inherently distributed and also maintains the multidimensionality of data. Our focus is on structured P2P systems that share spatial information. We present SPATIALP2P, a totally decentralized indexing and searching framework that is suitable for spatial data. SPATIALP2P supports P2P applications in which spatial information of various sizes can be dynamically inserted or deleted, and peers can join or leave. The proposed technique preserves well locality and directionality of space. Index Terms--Peer-to-peer, structured overlays, distributed hash tables, spatial data.

Published
2009

46. Meshing streaming updates with persistent data in an active data warehouse

Author

Polyzotis, Neoklis, Skiadopoulos, Spiros, Vassiliadis, Panos, Simitsis, Alkis, and Frantzell, Nils-Erik

Subjects
Algorithms -- Usage, Data warehousing -- Management, Streaming media -- Management, Knowledge management -- Research, Company business management, Algorithm, Data warehousing/data mining, Streaming media technology, Knowledge management, Business, Computers, Electronics, Electronics and electrical industries
Abstract

Active Data Warehousing has emerged as an alternative to conventional warehousing practices in order to meet the high demand of applications for up-to-date information. In a nutshell, an active warehouse is refreshed online and thus achieves a higher consistency between the stored information and the latest data updates. The need for online warehouse refreshment introduces several challenges in the implementation of data warehouse transformations, with respect to their execution time and their overhead to the warehouse processes. In this paper, we focus on a frequently encountered operation in this context, namely, the join of a fast stream S of source updates with a disk-based relation R, under the constraint of limited memory. This operation lies at the core of several common transformations such as surrogate key assignment, duplicate detection, or identification of newly inserted tuples. We propose a specialized join algorithm, termed mesh join (MESH JOIN), which compensates for the difference in the access cost of the two join inputs by 1) relying entirely on fast sequential scans of R and 2) sharing the I/O cost of accessing R across multiple tuples of S. We detail the MESHJOIN algorithm and develop a systematic cost model that enables the tuning of MESHJOIN for two objectives: maximizing throughput under a specific memory budget or minimizing memory consumption for a specific throughput. We present an experimental study that validates the performance of MESH JOIN on synthetic and real-life data. Our results verify the scalability of MESHJOIN to fast streams and large relations and demonstrate its numerous advantages over existing join algorithms. Index Terms--Active data warehouse, join, MESH JOIN, streams, relations.

Published
2008

47. A family of directional relation models for extended objects

Author

Skiadopoulos, Spiros, Sarkas, Nikos, Sellis, Timos, and Koubarakis, Manolis

Subjects
Family studies -- Analysis, Geographic information systems -- Analysis, Spatial systems -- Usage, Spatial systems -- Analysis, Geographic information system, Business, Computers, Electronics, Electronics and electrical industries
Abstract

In this paper, we introduce a family of expressive models for qualitative spatial reasoning with directions. The proposed family is based on the cognitive plausible cone-based model. We formally define the directional relations that can be expressed in each model of the family. Then, we use our formal framework to study two interesting problems: computing the inverse of a directional relation and composing two directional relations. For the composition operator, in particular, we concentrate on two commonly used definitions, namely, consistency-based and existential composition. Our formal framework allows us to prove that our solutions are correct. The presented solutions are handled in a uniform manner and apply to all of the models of the family. Index Terms--Spatial databases and GIS, cone-based directional relations, inverse and composition operators.

Published
2007

50. Logic and computational complexity for Boolean information retrieval

Author

Koubarakis, Manolis, Skiadopoulos, Spiros, and Tryfonopoulos, Christos

Subjects
Computational complexity -- Analysis, Query languages -- Usage, Information storage and retrieval -- Models, Business, Computers, Electronics, Electronics and electrical industries
Abstract

We study the complexity of query satisfiability and entailment for the Boolean Information Retrieval models WP and AWP using techniques from propositional logic and computational complexity. WP and AWP can be used to represent and query textual information under the Boolean model using the concept of attribute with values of type text, the concept of word, and word proximity constraints. Variations of WP and AWP are in use in most deployed digital libraries using the Boolean model, text extenders for relational database systems (e.g., Oracle 10g), search engines, and P2P systems for information retrieval and filtering. Index Terms--Boolean information retrieval, computational complexity, data models, query languages, satisfiability, entailment, proximity.

Published
2006

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