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Full-Text Articles in Computer Engineering

Lifetime Lexical Variation In Social Media, Lizi Liao, Jing Jiang, Ying Ding, Heyan Huang, Ee-Peng Lim Jul 2014

Lifetime Lexical Variation In Social Media, Lizi Liao, Jing Jiang, Ying Ding, Heyan Huang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

As the rapid growth of online social media attracts a large number of Internet users, the large volume of content generated by these users also provides us with an opportunity to study the lexical variation of people of different ages. In this paper, we present a latent variable model that jointly models the lexical content of tweets and Twitter users' ages. Our model inherently assumes that a topic has not only a word distribution but also an age distribution. We propose a Gibbs-EM algorithm to perform inference on our model. Empirical evaluation shows that our model can learn meaningful age-specific …


Where Are We In Wastewater Treatment Plants Data Management? A Review And A Proposal, Manel Poch, Joaquim Comas, José Porro, Manel Garrido-Baserba, Lluis Corominas, Maite Pijuan Jun 2014

Where Are We In Wastewater Treatment Plants Data Management? A Review And A Proposal, Manel Poch, Joaquim Comas, José Porro, Manel Garrido-Baserba, Lluis Corominas, Maite Pijuan

International Congress on Environmental Modelling and Software

Wastewater treatment plants (WWTP) are comprised of complex processes that need to be optimally managed. To attain that, in the last years an impressive effort has been made to incorporate monitoring devices able to provide from several hundred to more than ten thousand signals. With the aim to take benefit of those data, different data mining techniques have been applied to transform them into information and knowledge in order to help WWTP's managers. Furthermore, several mathematical models have been developed intending to simulate process behaviour including biomass and pollutants transformation. However, it is recognized that this it is not enough …


Pre-Processing Techniques Applied To Automatic Taxon Identification On Fish Otoliths, Ramon Reig-Bolaño, Pere Marti-Puig Jun 2014

Pre-Processing Techniques Applied To Automatic Taxon Identification On Fish Otoliths, Ramon Reig-Bolaño, Pere Marti-Puig

International Congress on Environmental Modelling and Software

This paper analyzes the characteristics of a rotation-invariant Feature space to be used in a classifier of fish otoliths, it is compared to two other Feature spaces, one with raw data and another with transformed data (using the Elliptic Fourier Descriptors EFD). Otoliths are found in the inner ear of fish. Their shape can be analyzed to determine sex, age, populations and species, and thus they can provide necessary and relevant information for ecological studies. The Automatic Taxon Identifier (ATI) is used to classify fish otoliths directly from a query image and is implemented on-line in a Public Database. This …


Text Stylometry For Chat Bot Identification And Intelligence Estimation., Nawaf Ali May 2014

Text Stylometry For Chat Bot Identification And Intelligence Estimation., Nawaf Ali

Electronic Theses and Dissertations

Authorship identification is a technique used to identify the author of an unclaimed document, by attempting to find traits that will match those of the original author. Authorship identification has a great potential for applications in forensics. It can also be used in identifying chat bots, a form of intelligent software created to mimic the human conversations, by their unique style. The online criminal community is utilizing chat bots as a new way to steal private information and commit fraud and identity theft. The need for identifying chat bots by their style is becoming essential to overcome the danger of …


Using The K-Means Clustering Algorithm To Classify Features For Choropleth Maps, Mark Polczynski, Michael Polczynski Apr 2014

Using The K-Means Clustering Algorithm To Classify Features For Choropleth Maps, Mark Polczynski, Michael Polczynski

Electrical and Computer Engineering Faculty Research and Publications

Common methods for classifying choropleth map features typically form classes based on a single feature attribute. This technical note reviews the use of the k-means clustering algorithm to perform feature classification using multiple feature attributes. The k-means clustering algorithm is described and compared to other common classification methods, and two examples of choropleth maps prepared using k-means clustering are provided.


Hot Zone Identification: Analyzing Effects Of Data Sampling On Spam Clustering, Rasib Khan, Mainul Mizan, Ragib Hasan, Alan Sprague Jan 2014

Hot Zone Identification: Analyzing Effects Of Data Sampling On Spam Clustering, Rasib Khan, Mainul Mizan, Ragib Hasan, Alan Sprague

Journal of Digital Forensics, Security and Law

Email is the most common and comparatively the most efficient means of exchanging information in today's world. However, given the widespread use of emails in all sectors, they have been the target of spammers since the beginning. Filtering spam emails has now led to critical actions such as forensic activities based on mining spam email. The data mine for spam emails at the University of Alabama at Birmingham is considered to be one of the most prominent resources for mining and identifying spam sources. It is a widely researched repository used by researchers from different global organizations. The usual process …


M-Fdbscan: A Multicore Density-Based Uncertain Data Clustering Algorithm, Atakan Erdem, Taflan İmre Gündem Jan 2014

M-Fdbscan: A Multicore Density-Based Uncertain Data Clustering Algorithm, Atakan Erdem, Taflan İmre Gündem

Turkish Journal of Electrical Engineering and Computer Sciences

In many data mining applications, we use a clustering algorithm on a large amount of uncertain data. In this paper, we adapt an uncertain data clustering algorithm called fast density-based spatial clustering of applications with noise (FDBSCAN) to multicore systems in order to have fast processing. The new algorithm, which we call multicore FDBSCAN (M-FDBSCAN), splits the data domain into c rectangular regions, where c is the number of cores in the system. The FDBSCAN algorithm is then applied to each rectangular region simultaneously. After the clustering operation is completed, semiclusters that occur during splitting are detected and merged to …


Discovery Of Hydrometeorological Patterns, Mete Çeli̇k, Fi̇li̇z Dadaşer Çeli̇k, Ahmet Şaki̇r Dokuz Jan 2014

Discovery Of Hydrometeorological Patterns, Mete Çeli̇k, Fi̇li̇z Dadaşer Çeli̇k, Ahmet Şaki̇r Dokuz

Turkish Journal of Electrical Engineering and Computer Sciences

Hydrometeorological patterns can be defined as meaningful and nontrivial associations between hydrological and meteorological parameters over a region. Discovering hydrometeorological patterns is important for many applications, including forecasting hydrometeorological hazards (floods and droughts), predicting the hydrological responses of ungauged basins, and filling in missing hydrological or meteorological records. However, discovering these patterns is challenging due to the special characteristics of hydrological and meteorological data, and is computationally complex due to the archival history of the datasets. Moreover, defining monotonic interest measures to quantify these patterns is difficult. In this study, we propose a new monotonic interest measure, called the hydrometeorological …


An Urgent Precaution System To Detect Students At Risk Of Substance Abuse Through Classification Algorithms, Faruk Bulut, İhsan Ömür Bucak Jan 2014

An Urgent Precaution System To Detect Students At Risk Of Substance Abuse Through Classification Algorithms, Faruk Bulut, İhsan Ömür Bucak

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, the use of addictive drugs and substances has turned out to be a challenging social problem worldwide. The illicit use of these types of drugs and substances appears to be increasing among elementary and high school students. After becoming addicted to drugs, life becomes unbearable and gets even worse for their users. Scientific studies show that it becomes extremely difficult for an individual to break this habit after being a user. Hence, preventing teenagers from addiction becomes an important issue. This study focuses on an urgent precaution system that helps families and educators prevent teenagers from developing …