Showing 73–84 of 776 results
A Web Search Engine-Based Approach to Measure Semantic Similarity between Words Abstract? A Web Search Engine-Based Approach to Measure Semantic Similarity between Words. Measuring the semantic similarity between words is an important component in various tasks on the web such as relation extraction, community mining, < Final Year Projects > document clustering, and automatic metadata…
A Workflow Management System for Scalable Data Mining on Clouds Abstract-The extraction of useful information from data is often a complex process that can be conveniently modeled as a data analysis workflow. When very large data sets must be analyzed and/or complex data mining algorithms must be executed, data analysis workflows may take very long…
Accuracy-Constrained Privacy-Preserving Access Control Mechanism for Relational Data Abstract? Accuracy-Constrained Privacy-Preserving Access Control Mechanism for Relational Data. Access control mechanisms protect sensitive information from unauthorized users. However, when sensitive information is shared and a Privacy Protection Mechanism (PPM) is not in place, an authorized user can still compromise the privacy of a person leading to…
Accuracy-Constrained Privacy-Preserving Access Control Mechanism for Relational Data Accuracy-Constrained Privacy-Preserving Access Control Mechanism for Relational Data. Access control mechanisms protect sensitive information from unauthorized users. However, when sensitive information is shared and a Privacy Protection Mechanism (PPM) is not in place, an authorized user can still compromise the privacy of a person leading to identity…
ACID: association correction for imbalanced data in GWAS Abstract-Genome-wide association study (GWAS) has been widely witnessed as a powerful tool for revealing suspicious loci from various diseases. However, real world GWAS tasks always suffer from the data imbalance problem of sufficient control samples and limited case samples. This imbalance issue can cause serious biases to…
Active Learning for Ranking through Expected Loss Optimization Abstract? Active Learning for Ranking through Expected Loss Optimization. Learning to rank arises in many data mining applications, ranging from web search engine, online advertising to recommendation system. In learning to rank, the performance of a ranking model is strongly affected by the number of labeled examples…
Active Learning of Constraints for Semi-Supervised Clustering Abstract?Active Learning of Constraints for Semi-Supervised Clustering. Semi-supervised clustering aims to improve clustering performance by considering user supervision in the form of pairwise constraints. In this paper, we study the active learning problem of selecting pairwise must-link and cannot-link constraints for semi-supervised clustering. We consider active learning in…
Adaptive and Energy Efficient Context Abstract? Adaptive and Energy Efficient Context. This paper presents a novel framework that includes an inhomogeneous (time-variant) Hidden Markov Model (HMM) and learning from data concepts. The framework either recognizes or estimates user contextual inferences called `user states’ within the concept of Human Activity Recognition (HAR) for future context-aware <...
Adaptive and Random Partitioning Software Testing Abstract?Random testing (RT) and subdomain testing are two major software testing strategies. Their simplicity makes them likely the most efficient testing strategies with respect to the time required for test case selection. However, the disadvantage of RT is its defect detection effectiveness. Adaptive testing (AT) is a feedback-based software…
Adaptive Processing for Distributed Skyline Queries over Uncertain Data Abstract? Query processing over uncertain data has gained growing attention, because it is necessary to deal with uncertain data in many real-life applications. In this paper, we investigate skyline queries over uncertain data in distributed environments < Final Year Projects 2016 > DSUD query whose research…
Adaptive Solitary Pulmonary Nodule Segmentation for Digital Radiography Images Based on Random Walks and Sequential Filter Abstract-Solitary pulmonary nodules (SPN) in digital radiography (DR) images often have unclear contours and infiltration, which make it a challenging task for traditional segmentation models to get satisfactory segmentation results. To overcome this challenge, this paper has proposed an…
Adding Geospatial Data Provenance into SDI?A Service-Oriented Approach Abstract? Geospatial data provenance records the derivation history of a geospatial data product. It is important in evaluating the quality of data products. In a Geospatial Web Service environment where data are often disseminated and processed widely and frequently in an unpredictable way, it is even more…
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