29 Result(s)
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Article
Vincent S. Tseng
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Open AccessExtracting Stock Predictive Information in Mutual Fund Managers’ Portfolio Decisions Through Machine Learning with Hypergraph
This paper proposes a machine learning framework that incorporates mutual fund managers’ portfolio decisions to predict stock price movements. It employs a weighted hypergraph to connect the information of the...
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A multi-label transformer-based deep learning approach to predict focal visual field progression
Tracking functional changes in visual fields (VFs) through standard automated perimetry remains a clinical standard for glaucoma diagnosis. This study aims to develop and evaluate a deep learning (DL) model to...
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Open AccessComparisons of deep learning algorithms for diagnosing bacterial keratitis via external eye photographs
Bacterial keratitis (BK), a painful and fulminant bacterial infection of the cornea, is the most common type of vision-threatening infectious keratitis (IK). A rapid clinical diagnosis by an ophthalmologist ma...
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Open AccessA deep learning approach in diagnosing fungal keratitis based on corneal photographs
Fungal keratitis (FK) is the most devastating and vision-threatening microbial keratitis, but clinical diagnosis a great challenge. This study aimed to develop and verify a deep learning (DL)-based corneal pho...
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Discovering negative comments by sentiment analysis on web forum
Social media enables people to communicate with each other on the Internet in real-time and rich styles. In other words, there is a lot of information on the social media. If we can extract negative opinions o...
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Efficiently mining uncertain high-utility itemsets
Data mining consists of deriving implicit, potentially meaningful and useful knowledge from databases such as information about the most profitable items. High-utility itemset mining (HUIM) has thus emerged as...
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EFIM: a fast and memory efficient algorithm for high-utility itemset mining
In recent years, high-utility itemset mining has emerged as an important data mining task. However, it remains computationally expensive both in terms of runtime and memory consumption. It is thus an important...
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Integrating tourist packages and tourist attractions for personalized trip planning based on travel constraints
In recent years, with the upgrading of mobile positioning and the popularity of smart devices, location related research gets a lot of attentions. One of popular issues is the trip planning problem. Although m...
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Open AccessAligning to the sample-specific reference sequence to optimize the accuracy of next-generation sequencing analysis for hepatitis B virus
Hepatitis B virus (HBV) quasispecies are crucial in the pathogenesis of chronic liver disease. Next-generation sequencing (NGS) is powerful for identifying viral quasispecies. To improve map** quality and si...
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Weighted frequent itemset mining over uncertain databases
Frequent itemset mining (FIM) is a fundamental research topic, which consists of discovering useful and meaningful relationships between items in transaction databases. However, FIM suffers from two important ...
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Open AccessMiningABs: mining associated biomarkers across multi-connected gene expression datasets
Human disease often arises as a consequence of alterations in a set of associated genes rather than alterations to a set of unassociated individual genes. Most previous microarray-based meta-analyses identifie...
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An efficient projection-based indexing approach for mining high utility itemsets
Recently, utility mining has widely been discussed in the field of data mining. It finds high utility itemsets by considering both profits and quantities of items in transactional data sets. However, most of t...
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Efficient algorithms for discovering high utility user behavior patterns in mobile commerce environments
Mining user behavior patterns in mobile environments is an emerging topic in data mining fields with wide applications. By integrating moving paths with purchasing transactions, one can find the sequential pur...
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Open AccessAn efficient method for mining cross-timepoint gene regulation sequential patterns from time course gene expression datasets
Observation of gene expression changes implying gene regulations using a repetitive experiment in time course has become more and more important. However, there is no effective method which can handle such kin...
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Time series pattern discovery by a PIP-based evolutionary approach
Time series are an important and interesting research field due to their many different applications. In our previous work, we proposed a time-series segmentation approach by combining a clustering technique, ...
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A hybrid scheme for energy-efficient object tracking in sensor networks
Energy saving is a critical issue in many sensor-network-based applications. Among the existing sensor-network-based applications, the surveillance application has attracted extensive attention. Object trackin...
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Open AccessMining differential top-k co-expression patterns from time course comparative gene expression datasets
Frequent pattern mining analysis applied on microarray dataset appears to be a promising strategy for identifying relationships between gene expression levels. Unfortunately, too many itemsets (co-expressed ge...
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Mining interesting user behavior patterns in mobile commerce environments
Discovering user behavior patterns from mobile commerce environments is an essential topic with wide applications, such as planning physical shop** sites, maintaining e-commerce on mobile devices and managin...
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Preference-oriented mining techniques for location-based store search
With the development of wireless telecommunication technologies, a number of studies have been done on the issues of location-based services due to wide applications. Among them, one of the active topics is th...
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Societally connected multimedia across cultures
The advance of the Internet in the past decade has radically changed the way people communicate and collaborate with each other. Physical distance is no more a barrier in online social networks, but cultural d...
