Computer Engineering Commons^™

Analyzing And Modeling Users In Multiple Online Social Platforms, Roy Lee Ka Wei

Dissertations and Theses Collection (Open Access)

This dissertation addresses the empirical analysis on user-generated data from multiple online social platforms (OSPs) and modeling of latent user factors in multiple OSPs setting.

In the first part of this dissertation, we conducted cross-platform empirical studies to better understand user's social and work activities in multiple OSPs. In particular, we proposed new methodologies to analyze users' friendship maintenance and collaborative activities in multiple OSPs. We also apply the proposed methodologies on real-world OSP datasets, and the findings from our empirical studies have provided us with a better understanding on users' social and work activities which are previously not uncovered …

Keyword-Based Patent Citation Prediction Via Information Theory, Farshad Madani, Martin Zwick, Tugrul U. Daim

Engineering and Technology Management Faculty Publications and Presentations

Patent citation shows how a technology impacts other inventions, so the number of patent citations (backward citations) is used in many technology prediction studies. Current prediction methods use patent citations, but since it may take a long time till a patent is cited by other inventors, identifying impactful patents based on their citations is not an effective way. The prediction method offered in this article predicts patent citations based on the content of patents. In this research, Reconstructability Analysis (RA), which is based on information theory and graph theory, is applied to predict patent citations based on keywords extracted from …

Domain-Specific Use Cases For Knowledge-Enabled Social Media Analysis, Soon Jye Kho, Swati Padhee, Goonmeet Bajaj, Krishnaprasad Thirunarayan, Amit Sheth

Publications

No abstract provided.

Clustering Method Based On Graph Data Model And Reliability Detection, Yanyun Cheng, Huisong Bian, Changsheng Bian

Journal of System Simulation

Abstract: For the data in feature space, traditional clustering algorithm can take clustering analysis directly. High-dimensional spatial data cannot achieve intuitive and effective graphical visualization of clustering results in 2D plane. Graph data can clearly reflect the similarity relationship between objects. According to the distance of the data objects, the feature space data are modeled as graph data by iteration. Cluster analysis based on modularity is carried out on the modeling graph data. The two-dimensional visualization of non-spherical-shape distribution data cluster and result is achieved. The concept of credibility of the clustering result is proposed, and a method is proposed, …

Horse Racing Prediction Using Graph-Based Features., Mehmet Akif Gulum

Electronic Theses and Dissertations

This thesis presents an applied horse racing prediction using graph based features on a set of horse races data. We used artificial neural network and logistic regression models to train then test to prediction without graph based features and with graph based features. This thesis can be explained in 4 main parts. Collect data from a horse racing website held from 2015 to 2017. Train data to using predictive models and make a prediction. Create a global directed graph of horses and extract graph-based features (Core Part) . Add graph based features to basic features and train to using same …

Maintainability Analysis Of Mining Trucks With Data Analytics., Abdulgani Kahraman

Electronic Theses and Dissertations

The mining industry is one of the biggest industries in need of a large budget, and current changes in global economic challenges force the industry to reduce its production expenses. One of the biggest expenditures is maintenance. Thanks to the data mining techniques, available historical records of machines’ alarms and signals might be used to predict machine failures. This is crucial because repairing machines after failures is not as efficient as utilizing predictive maintenance. In this case study, the reasons for failures seem to be related to the order of signals or alarms, called events, which come from trucks. The …

Real-Time Power System Dynamic Security Assessment Based On Advanced Feature Selection For Decision Tree Classifiers, Qusay Al-Gubri, Mohd Aifaa Mohd Ariff

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a novel algorithm based on an advanced feature selection technique for the decision tree (DT) classifier to assess the dynamic security in a power system. The proposed methodology utilizes symmetrical uncertainty (SU) to reduce the data redundancy in a dataset for DT classifier-based dynamic security assessment (DSA) tools. The results show that SU reduces the dimension of the dataset used for DSA significantly. Subsequently, the approach improves the performance of the DT classifier. The effectiveness of the proposed technique is demonstrated on the modified IEEE 30-bus test system model. The results show that the DT classifier with …

Mintbase V2.0: A Comprehensive Database For Trna-Derived Fragments That Includes Nuclear And Mitochondrial Fragments From All The Cancer Genome Atlas Projects., Venetia Pliatsika, Phillipe Loher, Rogan Magee, Aristeidis G. Telonis, Eric R. Londin, Megumi Shigematsu, Yohei Kirino, Isidore Rigoutsos

Computational Medicine Center Faculty Papers

MINTbase is a repository that comprises nuclear and mitochondrial tRNA-derived fragments ('tRFs') found in multiple human tissues. The original version of MINTbase comprised tRFs obtained from 768 transcriptomic datasets. We used our deterministic and exhaustive tRF mining pipeline to process all of The Cancer Genome Atlas datasets (TCGA). We identified 23 413 tRFs with abundance of ≥ 1.0 reads-per-million (RPM). To facilitate further studies of tRFs by the community, we just released version 2.0 of MINTbase that contains information about 26 531 distinct human tRFs from 11 719 human datasets as of October 2017. Key new elements include: the ability …