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preprocessing Techniques for Clustering Arabic Text: Challenges and Future Directions

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2024年第8期15卷 1301-1314页

作者： Almutairi, Tahani Saifuddin, Shireen Alotaibi, Reem Sarhan, Shahendah Nassif, Sarah King Abdulaziz Univ Dept Informat Technol Jeddah Saudi Arabia

Arabic is a complex language for text analysis because of its orthographic features, rich synonyms, and semantic style. Thus, Arabic text must be prepared more carefully in the preprocessing stage for the analyzer to improve the quality of the results. Moreover, many preprocessing steps have been proposed to improve the text analyzer quality by reducing high dimensionality, selecting the proper features to describe the text, and enhancing the process speed. This paper deeply investigates and summarizes the use of Arabic preprocessing techniques in Arabic text in general and focuses in-depth on clustering. Moreover, it focuses on seven preprocesses that are now used to prepare Arabic and provides the available tools for each of them;the seven preprocess are tokenization, normalization, stopword removal, stemming, vectorization, lemmatization, and feature selection. In addition, this paper investigates any work that uses synonyms and semantic techniques for preprocessing to prepare the text or reduce the dimensionality of the clustering algorithm. Therefore, this survey investigated nine techniques for Arabic text preprocessing to identify the challenges in this area. Finally, this study aims to serve as a reference for researchers interested in this area, and ends with potential future research directions.

关键词： Keywords Arabic preprocessing Arabic language survey clustering Arabic analysis extensive [1] [10] [6]. Moreover preprocessing algorithms

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Nondestructive detection of adulterated wolfberry (Lycium Chinense) fruits based on hyperspectral imaging technology

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JOURNAL OF FOOD PROCESS ENGINEERING 2023年第4期46卷 e14293-e14293页

作者： Nirere, Adria Sun, Jun Kama, Rakhwe Atindana, Vincent Akolbire Nikubwimana, Felix Didier Dusabe, Keza Dominique Zhong, Yuhao Jiangsu Univ Sch Elect & Informat Engn Zhenjiang Jiangsu Peoples R China CAAS Inst Farmland Irrigat Xinxing Peoples R China Jiangsu Univ Automot Engn Res Inst Zhenjiang Jiangsu Peoples R China Maharishi Int Univ Fairfield IA USA Jiangsu Univ Sch Food Sci & Biol Engn Zhenjiang Jiangsu Peoples R China Jiangsu Univ Sch Elect & Informat Engn Zhenjiang 212013 Jiangsu Peoples R China

In order to detect adulterants on Lycium Chinense species effectively, a rapid, clean, and nondestructive detection method based on hyperspectral imaging (HSI) technology was conducted in a wavelength range of 400.68-1001.60 nm. Industrial sulfur particles were chosen as a dye to prepare three groups of adulterated L. Chinense samples as the research object. The whole L. Chinense was considered the region of interest. First, a multiple scatter correction (MSC) method was used to preprocess spectra data. The competitive adaptive reweighted sampling (CARS) and linear discriminant analysis approaches were contrasted for optimal extraction of wavelengths characteristic. Then, two models were established: K-nearest neighbor (KNN) and support vector machine (SVM). Furthermore, the performance accuracies of KNN and SVM models were compared. According to the outcomes, the SVM model built on CARS provided the best classification impact. The accuracy for the prediction set was 98.75%, and the accuracy for the training set was 100%. Also, the kernel parameters c and g of the SVM model were enhanced by genetic algorithm (GA) optimization. The values parameters (c, g) were set at 14.975 and 0.224, respectively, and the results improved by 1.25% at an elapsed time of 1.887 s, with the accuracy reaching 100% on both training and test sets. This study aimed to detect and classify sulfur-adulterated wolfberries using an improved SVM and HSI. Finally, the results demonstrate that a combination of HSI and the CARS-GA-SVM model could be used for the rapid detection of foreign entities' in wolfberry *** applicationsDried wolfberry adulteration has a direct link to the overall quality of the fruits, and potentially compromises the health of the fruits consumers. The traditional methods of testing adulterants on Lycium Chinense are arduous, require a lot of time, and are highly impacted by biased elements, necessitating new techniques. HSI technology, on the other hand, is no

关键词： adulterated Lycium Chinense hyperspectral images preprocessing algorithms support vector machine wavelength selection algorithms

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Dealing with difficult minority labels in imbalanced mutilabel data sets

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NEUROCOMPUTING 2019年 326卷 39-53页

作者： Charte, Francisco Rivera, Antonio J. del Jesus, Maria J. Herrera, Francisco Univ Granada Dept Comp Sci & AI Granada 18071 Spain Univ Jaen Dept Comp Sci Jaen 23071 Spain

Multilabel classification is an emergent data mining task with a broad range of real world applications. Learning from imbalanced multilabel data is being deeply studied latterly, and several resampling methods have been proposed in the literature. The unequal label distribution in most multilabel datasets, with disparate imbalance levels, could be a handicap while learning new classifiers. In addition, this characteristic challenges many of the existent preprocessing algorithms. Furthermore, the concurrence between imbalanced labels can make harder the learning from certain labels. These are what we call difficult labels. In this work, the problem of difficult labels is deeply analyzed, its influence in multilabel classifiers is studied, and a novel way to solve this problem is proposed. Specific metrics to assess this trait in multilabel datasets, called SCUMBLE (Score of ConcUrrence among iMBalanced LabEls) and SCUMBLELbl, are presented along with REMEDIAL (REsampling MultilabEl datasets by Decoupling highly ImbAlanced Labels), a new algorithm aimed to relax label concurrence. How to deal with this problem using the R mldr package is also outlined. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Multilabel classification Imbalanced classification preprocessing algorithms Label concurrence

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Performance comparison of designated preprocessing white light interferometry algorithms on emerging multi- and many-core architectures

Performance comparison of designated preprocessing white lig...

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International Conference on Computational Science (ICCS) on the Ascent of Computational Excellence

作者： Schneider, Max Fey, Dietmar Kapusi, Daniel Machleidt, Torsten Univ Erlangen Nurnberg Chair Comp Sci Computer Architecture 3 Erlangen Germany Tech Univ Ilmenau Comp Graph Grp Ilmenau Germany GBS mbH Ilmenau Germany ZBS e V Ilmenau Germany

Parallel computing has been a niche for scientific research in academia for decades. However, as common industrial applications become more and more performance demanding and raising the clock frequency of conventional single-core systems is hardly an option due to reaching technological limitations, efficient use of multi-core CPUs has become imperative. 3D surface analysis of objects using the white light interferometry presents one of such computationally challenging applications. In this article three established preprocessing methods of white light interferometry data analysis are used to evaluate the suitability of three modern multi-core architectures - generic multi-core CPUs, GPGPUs and IBM's Cell BE. The results show that function offloading to GPGPUs, which offer independent memory and many hundreds of threads running in parallel, yields the highest performance compared to other systems. Furthermore, by outsourcing computational tasks to GPUs, the workload of other system resources, such as CPU or system memory, is reduced. This allows accelerated execution of other tasks, e. g. acquisition of images with higher frame rates.

关键词： White light interferometry preprocessing algorithms OpenMP IBM Cell BE CUDA GPGPU

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Performance comparison of designated preprocessing white light interferometry algorithms on emerging multi- and many-core architectures

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Procedia Computer Science 2011年 4卷 2037-2046页

作者： Max Schneider Dietmar Fey Daniel Kapusi Torsten Machleidt Chair of Computer Science 3 (Computer Architecture) Friedrich-Alexander-University of Erlangen-Nuremberg ZBS e.V. Ilmenau Computer Graphics Group Technical University of Ilmenau GBS mbH Ilmenau

关键词： White light interferometry preprocessing algorithms OpenMP IBM Cell BE CUDA GPGPU

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A Sensor Middleware for Integration of Heterogeneous Medical Devices

A Sensor Middleware for Integration of Heterogeneous Medical...

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32nd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBC 10)

作者： Brito, M. Vale, L. Carvalho, P. Henriques, J. Univ Coimbra Ctr Informat & Syst P-3000 Coimbra Portugal

ISBN: (纸本)9781424441242

In this paper, the architecture of a modular, service-oriented, Sensor Middleware for data acquisition and processing is presented. The described solution was developed with the purpose of solving two increasingly relevant problems in the context of modern pHealth systems: i) to aggregate a number of heterogeneous, off-the-shelf, devices from which clinical measurements can be acquired and ii) to provide access and integration with an 802.15.4 network of wearable sensors. The modular nature of the Middleware provides the means to easily integrate pre-processing algorithms into processing pipelines, as well as new drivers for adding support for new sensor devices or communication technologies. Tests performed with both real and artificially generated data streams show that the presented solution is suitable for use both in a Windows PC or a Windows Mobile PDA with minimal overhead.

关键词： IEEE 802.15.4 network biomedical electronics body area networks data acquisition data acquisition data processing heterogeneous device aggregation heterogeneous medical device integration medical signal processing middleware modern pHealth systems modular middleware modular sensor middleware personal area networks preprocessing algorithms processing pipelines sensor middleware architecture service oriented sensor middleware wearable computers wearable sensor network wireless sensor networks

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Outcomes of Gene Association Analysis of Cancer Microarray Data are Impacted by Pre-processing algorithms

Outcomes of Gene Association Analysis of Cancer Microarray D...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Baskaran, N. Kwoh, Chee Keong Hui, Kam M. Natl Canc Ctr Singapore Div Cellular & Mol Res 11 Hosp Dr Singapore 169610 Singapore Nanyang Technol Univ Sch Comp Engn Div Informat Syst Nanyang Ave Singapore 639798 Singapore

ISBN: (纸本)9781424483075

Gene association analysis of cancer microarray data provides a wealth of information on gene expression patterns and cancer pathways to enhance the identification of potential biomarkers for cancer diagnosis, prognosis, and prediction of therapeutic responsiveness. However, achieving these biological/clinical objectives relies heavily on the functional capabilities and accuracy of the various analytical tools to mine these cancer microarray gene expression profiles. Many preprocessing algorithms exist for analyzing Affymetrix microarray gene expression data. Previous studies have evaluated these algorithms on their capabilities in accurately determining gene expression using a variety of spike-in as well as experimental data sets. However, variations in detecting differentially expressed genes between these different pre-processing algorithms on a single cancer dataset have not been done in a systems-level evaluation. In this study, we assessed the comparability and the level of variation between PLIER, GCRMA, RMA and MAS5 for their capability to detect differentially expressed genes.

关键词： Differentially Expressed Genes GCRMA Gene Expression Profiling Human Hepatocellular Carcinoma (HCC) MAS5 Microarray Data preprocessing algorithms PLIER RMA

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Optimization of region of interest luminances may enhance radiologists' light adaptation

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ACADEMIC RADIOLOGY 2008年第4期15卷 488-493页

作者： O'Connell, Niamh M. Toomey, Rachel J. McEntee, Mark Ryan, John Stowe, John Adams, Adrian Brennan, Patrick C. UCD Sch Med & Med Sci Dublin 4 Ireland Mater Misericordiae Univ Hosp Dublin Ireland

Rationale and Objectives. Radiologic image details are best discriminated at luminance levels to which the eye is adapted. Recommendations that ambient light conditions are matched to overall monitor luminance to encourage appropriate adaptation are based on an assumption that clinically significant regions within the image match average monitor luminance. The current work examines this assumption. Materials and Methods. Three image types were considered: posteroanterior (PA) chest;PA wrist;and computed tomography (CT) head. Luminance at clinically significant regions was measured at hilar region and peripheral lung (chest), distal radius (wrist), and supraventricular white matter (head). Average monitor luminances were calculated from measurements at 16 regions of the display face plate. Three ambient light levels-30, 100 and 400 lux-were employed. Thirty samples of each image type were used. Results. Statistically significant differences were noted between average monitor luminances and clinically important regions of interest of up to a factor of 3.8, 2, and 6.3 for chest, wrist, and CT head images respectively (P <.0001). Values for the hilum of the chest and distal radius were higher than average monitor levels, whereas the reverse was observed for the peripheral lung and CT brain. Increasing ambient light had no impact on results. Conclusions. Clinically important radiologic information for common radiologic examinations is not being presented to observers in a way that facilitates optimized adaptation. This may have a significant impact on the ability of the observer to identify details with low contrast discriminability. The importance of image-processing algorithms focussing on clinically significant abnormalities rather than anatomic regions is highlighted.

关键词： preprocessing algorithms abnormality-specific display

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Performance benefits for adults using a cochlear implant with adaptive dynamic range optimization (ADRO): A comparative study

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Cochlear Implants International 2008年第1期9卷 8-26页

作者： Müller-Deile, J. Kiefer, J. Wyss, J. Nicolai, J. Battmer, Roft Dieter Christian-Albrechts-University Kiel Kiel Germany JW Goethe University of Frankfurt am Main Frankfurt am Main Germany Cochlear AG Basel Basel Switzerland Department of Otolaryngology Medizinische Hochschule Hannover Hannover Germany

The aim of this study was to assess the qualitative and quantitative benefits for speech-recognition ability of a preprocessing strategy known as adaptive dynamic range optimization (ADRO), used in conjunction with the subject's standard MAP, in comparison with the subject's standard MAP alone, for a group of experienced German-speaking adults using the Nucleus® 24 Cochlear implant. In a prospective, single-subject, comparative study design, experienced adult CI-users were asked to trial and compare both their standard MAP and the newly fitted ADRO MAP (ADRO MAP fitting - week 0) following a take-home trial period of 5 weeks. Assessment of speech recognition ability performed in quiet (at 50, 60 and 70 dB SPL) and adaptively in noise was carried out repeatedly in two test sessions in weeks 5 and 7 (ADRO MAP postfitting) using both MAPs. The order of speech tests and MAPs tested was counterbalanced across the test sessions to control for potential learning effects during the study. Subjective assessments were performed at week 0 to assess details of current usage. Comparative subjective assessments were carried out at weeks 5 and 7 to obtain impressions of loudness of environmental sounds and speech understanding in a variety of conversational situations with both MAPs and finally MAP preference judgements. Fifteen adult, German-speaking, experienced implant users wearing their body-worn SPrint processor for a minimum of six hours and up to 16 hours per day were enrolled in the study across three university clinic hospitals in Germany. On average, speech-reception thresholds (SRT) were significantly improved with the ADRO MAP compared to using the standard MAP for all speech materials in quiet. The mean advantage for SRT values with the ADRO MAP was 2.9 dB, (Y σ ± 2.8 dB (P = 0.002) for the Freiburger Numbers test and 3.3 dB, σ ± 3.2 dB (p = 0.008) for the Freiburger Monosyllabic Words test. In noise, the ADRO MAP led to a significant improvement for the group for th

关键词： ADRO preprocessing algorithms Soft speech Speech in noise Speech understanding Subjective assessments

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