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Stance Detection of Turkish Twitter Accounts
2023 31st Signal Processing and Communications Applications Conference (SIU)
Year: 2023 | Conference Paper |
Twitter offers users an environment where they can express their opinions on any subject. As a result, user activities have become an important resource for various sociological studies. In this study, we proposed machine learning methods that utilize text-based and interaction-based features to predict the opinions of users who post messages in Turkish. We also performed zero-shot classification ...Show More
Geospatial Radar Deployment Optimization
2021 6th International Conference on Computer Science and Engineering (UBMK)
Year: 2021 | Conference Paper |
With the advancement of technology, many services have been developed that cover certain regions and provide benefits on various issues. Examples of these are internet providers, mobile hospitals, weather balloons and radars used by the army or navy. As the geography grows and the number of specified systems increases, it is expected that these will act as a whole and be optimally distributed. In ...Show More
Distinguishing True and False Buy/Sell Triggers from Financial Technical Indicators
2020 Innovations in Intelligent Systems and Applications Conference (ASYU)
Year: 2020 | Conference Paper |
The objective of this study is to develop a method to distinguish True and False Buy/Sell recommendations. Various recommendation schemes, like 30/70 RSI (Relative Strength Index) scheme, are effectively used by many traders. However, the triggers produced by such recommendation schemes are found suspicious most of the time, and hence are non-actionable. In this study we develop a dynamic programm...Show More
Inferring Political Alignments of Twitter Users
2018 International Symposium on Networks, Computers and Communications (ISNCC)
Year: 2018 | Conference Paper |
Cited by: Papers (6)
Increasing popularity of Twitter in politics is subject to commercial and academic interest. To fully exploit the merits of this platform, reaching target audience with desired political leanings is critical. This paper extends the research on inferring political orientations of Twitter users to the case of 2017 Turkish constitutional referendum. After constructing a targeted dataset of tweets, we...Show More
A top-down k-anonymization implementation for apache spark
2017 IEEE International Conference on Big Data (Big Data)
Year: 2017 | Conference Paper |
Cited by: Papers (14)
Data science continues to evolve with each passing day and upgrades itself according to the exponentially increasing amount of data. The progression provides convenience to extract meaningful information from the huge amount of data from various domains including individual, public health, micro-blogging and sensors. The ability to process huge volume of data and to extract valuable information so...Show More
End-to-end internet speed analysis of mobile networks with mapReduce
2016 International Symposium on Networks, Computers and Communications (ISNCC)
Year: 2016 | Conference Paper |
Cited by: Papers (2)
Packet-based mobile networks are increasingly carrying internet traffic mostly for data intensive-applications. Mobile internet usage, with 67% share worldwide, is very important for mobile users. Because of the explosive growth of mobile data usage demand, data speed analysis is a very essential way to characterize network quality and user experience for service providers. Key Performance Indicat...Show More
REFBSS: Reference based similarity search in biological network databases
2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
Year: 2015 | Conference Paper |
Cited by: Papers (1)
Biological networks, mostly abstracted as graphs, are key to many important activities inside the cell. Similarity-based analysis is one of the techniques for understanding the role of a query network. In that context, a database consisting of biological networks is aligned with a query network and the networks having a similarity score higher and lower than a predefined cutoff value are separated...Show More
Privacy-Preserving Sharing of Sensitive Semantic Locations under Road-Network Constraints
Emre Yigitoglu;Maria Luisa Damiani;Osman Abul;Claudio Silvestri
2012 IEEE 13th International Conference on Mobile Data Management
Year: 2012 | Conference Paper |
Cited by: Papers (35)
This paper presents a privacy-preserving framework for the protection of sensitive positions in real time trajectories. We assume a scenario in which the sensitivity of user's positions is space-varying, and so depends on the spatial context, while the user's movement is confined to road networks and places. Typical users are the non-anonymous members of a geo-social network who agree to share the...Show More
SAWLnet: Sensitivity Aware Location Cloaking on Road-NETworks
Claudio Silvestri;Emre Yigitoglu;Maria Luisa Damiani;Osman Abul
2012 IEEE 13th International Conference on Mobile Data Management
Year: 2012 | Conference Paper |
Cited by: Papers (3)
Location based queries are increasingly common in mobile applications, and the associated privacy issues have become a hot research topic in the last years. Most of the current approaches, however, do not account for the location of potentially sensitive places and for constraints on the movement of users, such as speed limits or network contraints. In this demo we present different deployment sce...Show More
Turkish archive digitization by human computation approach
2012 International Symposium on Innovations in Intelligent Systems and Applications
Year: 2012 | Conference Paper |
Cited by: Papers (3)
Human computation is a promising approach at solving computation tasks for which humans currently perform better than computers. Archive digitization is such a task. In this paper, we present our reCAPTCHA like archive digitization system, called trCAPTCHA, mainly targeting old Turkish archives and hence Turkish speaking audience. trCAPTCHA differs from reCAPTCHA that it uses no global dictionary ...Show More
Long Range Correlations between nucleotide triplets
Proceedings of the 6th International Symposium on Health Informatics and Bioinformatics
Year: 2011 | Conference Paper |
The study of statistical fluctuations in DNA sequences can reveal important characteristics of their organization. Particularly, in the last two decades, several studies have focused on the detection of Long Range Correlations (LRC) in DNA sequences, and on the study of particular long range dependence properties of nucleotides. Since protein coding is carried out by codons (nucleotide triplets), ...Show More
Sensitive knowledge hiding application
National Conference on Electrical, Electronics and Computer Engineering
Year: 2010 | Conference Paper |
Diverse organizations store their business related data in their own databases. Some of them publish their data as is to third parties for research purposes. However, this way of data sharing has the risk of disclosing sensitive knowledge which the database may entail. For safe publishing the database must be sanitized before sharing; so that no sensitive knowledge is conveyed. The process is know...Show More
Hiding Sequential and Spatiotemporal Patterns
The process of discovering relevant patterns holding in a database was first indicated as a threat to database security by O'Leary in. Since then, many different approaches for knowledge hiding have emerged over the years, mainly in the context of association rules and frequent item sets mining. Following many real-world data and application demands, in this paper, we shift the problem of knowledg...Show More
MotifHider: A knowledge hiding approach to sequence masking
2009 24th International Symposium on Computer and Information Sciences
Year: 2009 | Conference Paper |
Cited by: Papers (1)
In a typical de novo motif discovery process, it is quite common that many of the motif candidates output from motif discovery programs are either already known motifs or motif-like decoy/repeat patterns. To prevent the false discovery and also to increase the chance of authentic novel motif discovery, some motif discovery programs employ a pre-processing stage in order to mask certain repeat posi...Show More
Frequent itemsets hiding: A performance evaluation framework
2009 24th International Symposium on Computer and Information Sciences
Year: 2009 | Conference Paper |
Cited by: Papers (1)
Sensitive knowledge hiding is an essential requirement to prevent disclosure of any sensitive knowledge holding in shared databases. The security of a database may be risked when it is made public as is: because the data mining tools are so sophisticated that the sensitive knowledge can easily be surfaced by receivers. This gives rise to a sanitization process which transforms the original databas...Show More
Never Walk Alone: Uncertainty for Anonymity in Moving Objects Databases
2008 IEEE 24th International Conference on Data Engineering
Year: 2008 | Conference Paper |
Preserving individual privacy when publishing data is a problem that is receiving increasing attention. According to the fc-anonymity principle, each release of data must be such that each individual is indistinguishable from at least k - 1 other individuals. In this paper we study the problem of anonymity preserving data publishing in moving objects databases. We propose a novel concept of k-anon...Show More
Hiding Sensitive Trajectory Patterns
Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007)
Year: 2007 | Conference Paper |
Cited by: Papers (10)
Spatio-temporal traces left behind by moving individuals are increasingly available. On the one hand, mining this kind of data is expected to produce interesting behavioral knowledge enabling novel classes of mobility applications; but on the other hand, due to the peculiar nature of position data, mining it creates important privacy concerns. Thus, studying privacy preserving data mining methods ...Show More
Privacy-Aware Knowledge Discovery from Location Data
Maurizio Atzori;Francesco Bonchi;Fosca Giannotti;Dino Pedreschi;Osman Abul
2007 International Conference on Mobile Data Management
Year: 2007 | Conference Paper |
Cited by: Papers (1)
Spatio-temporal, geo-referenced datasets are growing rapidly, and will be more in the near future. This phenomenon is mostly due to the daily collection of telecommunication data from mobile phones and other location-aware devices and is expected to enable novel classes of applications based on the extraction of behavioral patterns from mobility data. Such patterns could be used for instance in tr...Show More
Hiding Sequences
2007 IEEE 23rd International Conference on Data Engineering Workshop
Year: 2007 | Conference Paper |
Cited by: Papers (21)
The process of discovering relevant patterns holding in a database, was first indicated as a threat to database security by O' Leary in [20]. Since then, many different approaches for knowledge hiding have emerged over the years, mainly in the context of association rules and frequent itemsets mining. Following many real-world data and applications demands, in this paper we shift, the problem of k...Show More
False Discovery Rates in Identifying Functional DNA Motifs
2007 IEEE 7th International Symposium on BioInformatics and BioEngineering
Year: 2007 | Conference Paper |
There are several methods for scoring a set of upstream DNA sequences against a given motif. Typically, significance of raw scores are based on p-values, measured by statistical hypothesis testing. As an extension, multiple hypothesis testing is adopted in cases where there are multiple motifs to be evaluated in parallel. In this way significant motifs are identified for a given significance level...Show More
Optimal Multi-Objective Control Method for Discrete Genetic Regulatory Networks
Sixth IEEE Symposium on BioInformatics and BioEngineering (BIBE'06)
Year: 2006 | Conference Paper |
Cited by: Papers (2)
In this paper, we study the control problem and note that it is multi-objective by nature, and thus we develop an optimal multi-objective approach. Our approach includes formalizing components and identifying dimensions, resulting in few cases for concrete problem formulation. For a selected case, namely the finite control case, a single-objective from the literature and our multi-objective soluti...Show More
A Powerful Approach for Effective Finding of Significantly Differentially Expressed Genes
The problem of identifying significantly differentially expressed genes for replicated microarray experiments is accepted as significant and has been tackled by several researchers. Patterns from gene expression (PaGE) and q-values are two of the well-known approaches developed to handle this problem. This paper proposes a powerful approach to handle this problem. We first propose a method for est...Show More
Markov decision processes based optimal control policies for probabilistic boolean networks
Proceedings. Fourth IEEE Symposium on Bioinformatics and Bioengineering
Year: 2004 | Conference Paper |
Cited by: Papers (6)
This paper addresses the control formulation process for probabilistic boolean genetic networks. It is a major problem that has not been investigated enough yet. We argue that a monitoring stage is necessary after the control stage for providing guidance about the evolution of the investigated state. For this purpose, we developed methods for generating optimal control policies for each of the fol...Show More
Cluster validity investigates whether generated clusters are true clusters or due to chance. This is usually done based on subsampling stability analysis. Related to this problem is estimating true number of clusters in a given dataset. There are a number of methods described in the literature to handle both purposes. In this paper, we propose three methods for estimating confidence in the validit...Show More
Multiagent reinforcement learning using function approximation
Learning in a partially observable and nonstationary environment is still one of the challenging problems in the area of multiagent (MA) learning. Reinforcement learning is a generic method that suits the needs of MA learning in many aspects. This paper presents two new multiagent based domain independent coordination mechanisms for reinforcement learning; multiple agents do not require explicit c...Show More
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