Search results for: Image Mining

Authors: Medjram Sofiane, Babahenini Mohamed Chaouki, Mohamed Benali Yamina

Abstract:

Skin detection is an important task for computer vision systems. A good method of skin detection means a good and successful result of the system. The colour is a good descriptor for image segmentation and classification; it allows detecting skin colour in the images. The lighting changes and the objects that have a colour similar than skin colour make the operation of skin detection difficult. In this paper, we proposed a method using the YCbCr colour space for skin detection and lighting effects elimination, then we use the information of texture to eliminate the false regions detected by the YCbCr skin model.

Keywords: Skin detection, YCbCr, GLCM, Texture, Human skin.

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Authors: Xiaohua Liu, Juan F. Beltran, Nishant Mohanchandra, Godfried T. Toussaint

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Support vector machines (SVMs) are considered to be the best machine learning algorithms for minimizing the predictive probability of misclassification. However, their drawback is that for large data sets the computation of the optimal decision boundary is a time consuming function of the size of the training set. Hence several methods have been proposed to speed up the SVM algorithm. Here three methods used to speed up the computation of the SVM classifiers are compared experimentally using a musical genre classification problem. The simplest method pre-selects a random sample of the data before the application of the SVM algorithm. Two additional methods use proximity graphs to pre-select data that are near the decision boundary. One uses k-Nearest Neighbor graphs and the other Relative Neighborhood Graphs to accomplish the task.

Keywords: Machine learning, data mining, support vector machines, proximity graphs, relative-neighborhood graphs, k-nearestneighbor graphs, random sampling, training data condensation.

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Authors: D. He, Y. Pang, G. Lodewijks

Abstract:

Belt conveyors play an important role in continuous dry bulk material transport, especially at the mining industry. Speed control is expected to reduce the energy consumption of belt conveyors. Transient operation is the operation of increasing or decreasing conveyor speed for speed control. According to literature review, current research rarely takes the conveyor dynamics in transient operation into account. However, in belt conveyor speed control, the conveyor dynamic behaviors are significantly important since the poor dynamics might result in risks. In this paper, the potential risks in transient operation will be analyzed. An existing finite element model will be applied to build a conveyor model, and simulations will be carried out to analyze the conveyor dynamics. In order to realize the soft speed regulation, Harrison’s sinusoid acceleration profile will be applied, and Lodewijks estimator will be built to approximate the required acceleration time. A long inclined belt conveyor will be studied with two major simulations. The conveyor dynamics will be given.

Keywords: Belt conveyor, speed control, transient operation, dynamics

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Authors: Sae-Rom Pak, Seung Hwan Park, Jeong Ho Cho, Daewoong An, Cheong-Sool Park, Jun Seok Kim, Jun-Geol Baek

Abstract:

It is important to predict yield in semiconductor test process in order to increase yield. In this study, yield prediction means finding out defective die, wafer or lot effectively. Semiconductor test process consists of some test steps and each test includes various test items. In other world, test data has a big and complicated characteristic. It also is disproportionably distributed as the number of data belonging to FAIL class is extremely low. For yield prediction, general data mining techniques have a limitation without any data preprocessing due to eigen properties of test data. Therefore, this study proposes an under-sampling method using support vector machine (SVM) to eliminate an imbalanced characteristic. For evaluating a performance, randomly under-sampling method is compared with the proposed method using actual semiconductor test data. As a result, sampling method using SVM is effective in generating robust model for yield prediction.

Keywords: Yield Prediction, Semiconductor Test Process, Support Vector Machine, Under Sampling

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Authors: S. Sarumathi, N. Shanthi, S. Vidhya

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In the present world, predicting rainfall is considered to be an essential and also a challenging task. Normally, the climate and rainfall are presumed to have non-linear as well as intricate phenomena. For predicting accurate rainfall, we necessitate advanced computer modeling and simulation. When there is an enhanced understanding of the spatial and temporal distribution of precipitation then it becomes enrichment to applications such as hydrologic, climatic and ecological. Conversely, there may be some kind of challenges occur in the community due to some application which results in the absence of consistent precipitation observation in remote and also emerging region. This survey paper provides a multifarious collection of methodologies which are epitomized by various researchers for predicting the rainfall. It also gives information about some technique to forecast rainfall, which is appropriate to all methods like numerical, traditional and statistical.

Keywords: Satellite Image, Segmentation, Feature Extraction, Classification, Clustering, Precipitation Estimation.

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Authors: C. C. D. Kulathilake, M. Jayatilake, T. Takahashi

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The myocardium is composed of specialized muscle which relies mainly on fatty acid and sugar metabolism and it is widely contribute to the heart functioning. The changes of the cardiac energy-producing system during heart failure have been proved using autoradiography techniques. This study focused on evaluating sugar and fatty acid metabolism in myocardium as cardiac energy getting system using heart-accumulated radiopharmaceuticals. Two sets of autoradiographs of heart cross sections of Lewis male rats were analyzed and the time- accumulation curve obtained with use of the MATLAB image processing software to evaluate fatty acid and sugar metabolic functions.

Keywords: Autoradiographs, fatty acid, radiopharmaceuticals and sugar.

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Authors: E. F. P. Leme, L. J. R. Lopez, D. G. Goroso

Abstract:

In this paper as showed a non-invasive 3D eye tracker for optometry clinical applications. Measurements of biomechanical variables in clinical practice have many font of errors associated with traditional procedments such cover test (CT), near point of accommodation (NPC), eye ductions (ED), eye vergences (EG) and, eye versions (ES). Ocular motility should always be tested but all evaluations have a subjective interpretations by practitioners, the results is based in clinical experiences, repeatability and accuracy don-t exist. Optometric-lab is a tool with 3 (tree) analogical video cameras triggered and synchronized in one acquisition board AD. The variables globe rotation angle and velocity can be quantified. Data record frequency was performed with 27Hz, camera calibration was performed in a know volume and image radial distortion adjustments.

Keywords: Eye Tracking, strabismus, eye movements, optometry.

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Authors: Chakkrit Snae

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Names are important in many societies, even in technologically oriented ones which use e.g. ID systems to identify individual people. Names such as surnames are the most important as they are used in many processes, such as identifying of people and genealogical research. On the other hand variation of names can be a major problem for the identification and search for people, e.g. web search or security reasons. Name matching presumes a-priori that the recorded name written in one alphabet reflects the phonetic identity of two samples or some transcription error in copying a previously recorded name. We add to this the lode that the two names imply the same person. This paper describes name variations and some basic description of various name matching algorithms developed to overcome name variation and to find reasonable variants of names which can be used to further increasing mismatches for record linkage and name search. The implementation contains algorithms for computing a range of fuzzy matching based on different types of algorithms, e.g. composite and hybrid methods and allowing us to test and measure algorithms for accuracy. NYSIIS, LIG2 and Phonex have been shown to perform well and provided sufficient flexibility to be included in the linkage/matching process for optimising name searching.

Keywords: Data mining, name matching algorithm, nominaldata, searching system.

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Authors: Ichihan Tai, Bill Olson, Paul Blessner

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Traditional early warning systems that alarm against crisis are generally based on structured or numerical data; therefore, a system that can make predictions based on unstructured textual data, an uncorrelated data source, is a great complement to the traditional early warning systems. The Chicago Board Options Exchange (CBOE) Volatility Index (VIX), commonly referred to as the fear index, measures the cost of insurance against market crash, and spikes in the event of crisis. In this study, news data is consumed for prediction of whether there will be a market-wide crisis by predicting the movement of the fear index, and the historical references to similar events are presented in an unsupervised manner. Topic modeling-based prediction and representation are made based on daily news data between 1990 and 2015 from The Wall Street Journal against VIX index data from CBOE.

Keywords: Early Warning System, Knowledge Management, Topic Modeling, Market Prediction.

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Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

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Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: Instance selection, data reduction, MapReduce, kNN.

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Authors: Witcha Chimphlee, Abdul Hanan Abdullah, Mohd Noor Md Sap, Siriporn Chimphlee, Surat Srinoy

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It is important problems to increase the detection rates and reduce false positive rates in Intrusion Detection System (IDS). Although preventative techniques such as access control and authentication attempt to prevent intruders, these can fail, and as a second line of defence, intrusion detection has been introduced. Rare events are events that occur very infrequently, detection of rare events is a common problem in many domains. In this paper we propose an intrusion detection method that combines Rough set and Fuzzy Clustering. Rough set has to decrease the amount of data and get rid of redundancy. Fuzzy c-means clustering allow objects to belong to several clusters simultaneously, with different degrees of membership. Our approach allows us to recognize not only known attacks but also to detect suspicious activity that may be the result of a new, unknown attack. The experimental results on Knowledge Discovery and Data Mining-(KDDCup 1999) Dataset show that the method is efficient and practical for intrusion detection systems.

Keywords: Network and security, intrusion detection, fuzzy cmeans, rough set.

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Authors: Shimal Das, Dibyendu Ghoshal

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The effect of directional search using iterated functional system has been studied on four images taken from databases. The images are portioned successively towards smaller dimension. Presented method provides the faster rate of convergence with respect to processing time in the flat region, but the same has been found to be slower at the border of the images and edges. It has also been revealed that the PSNR is lower at the edges and border portions of the image, and it is found to be higher in the uniform gray region, under the same external illumination and external noise environment.

Keywords: Iterated functional system, fractal compression, structural similarity index measure, fractal block coding, affine transformations.

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Authors: Farrukh Shahzad

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The rich Islamic resources related to religious text, Islamic sciences, and history are widely available in print and in electronic format online. However, most of these works are only available in Arabic language. In this research, an attempt is made to utilize these resources to create interactive web applications in Arabic, English and other languages. The system utilizes the Pattern Recognition, Knowledge Management, Data Mining, Information Retrieval and Management, Indexing, storage and data-analysis techniques to parse, store, convert and manage the information from authentic Arabic resources. These interactive web Apps provide smart multi-lingual search, tree based search, on-demand information matching and linking. In this paper, we provide details of application architecture, design, implementation and technologies employed. We also presented the summary of web applications already developed. We have also included some screen shots from the corresponding web sites. These web applications provide an Innovative On-line Learning Systems (eLearning and computer based education).

Keywords: Islamic resources, Muslim scholars, hadith, narrators, history, fiqh.

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Authors: M. Tridi, N. Nacereddine, N. Oucief

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This paper describes a novel method for automatic estimation of the contours of weld defect in radiography images. Generally, the contour detection is the first operation which we apply in the visual recognition system. Our approach can be described as a region based maximum likelihood formulation of parametric deformable contours. This formulation provides robustness against the poor image quality, and allows simultaneous estimation of the contour parameters together with other parameters of the model. Implementation is performed by a deterministic iterative algorithm with minimal user intervention. Results testify for the very good performance of the approach especially in synthetic weld defect images.

Keywords: Contour, gaussian, likelihood, rayleigh.

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Authors: Amdouni Hamida, Gammoudi Mohamed Mohsen

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In order to help the expert to validate association rules extracted from data, some quality measures are proposed in the literature. We distinguish two categories: objective and subjective measures. The first one depends on a fixed threshold and on data quality from which the rules are extracted. The second one consists on providing to the expert some tools in the objective to explore and visualize rules during the evaluation step. However, the number of extracted rules to validate remains high. Thus, the manually mining rules task is very hard. To solve this problem, we propose, in this paper, a semi-automatic method to assist the expert during the association rule's validation. Our method uses rule-based classification as follow: (i) We transform association rules into classification rules (classifiers), (ii) We use the generated classifiers for data classification. (iii) We visualize association rules with their quality classification to give an idea to the expert and to assist him during validation process.

Keywords: Association rules, Rule-based classification, Classification quality, Validation.

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Authors: Suriyon Tansuriyavong, Yuuta Suzuki, Boonmee Choompol

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Wheel-running type moving robot has the restriction on the moving range caused by obstacles or stairs. Solving this weakness, we studied the development of moving robot using airship. Our airship robot moves by recognizing arrow marks on the path. To have the airship robot recognize arrow marks, we used edge-based template matching. To control propeller units, we used PID and PD controller. The results of experiments demonstrated that the airship robot can move along the marks and can go up and down the stairs. It is shown the possibility that airship robot can become a robot which can move at wide range facilities.

Keywords: Template matching, moving robot, airship robot, PID control.

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Authors: Hadjira Bentoumi, Pascal Gautron, Kadi Bouatouch

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We present a method for fast volume rendering using graphics hardware (GPU). To our knowledge, it is the first implementation on the GPU. Based on the Shear-Warp algorithm, our GPU-based method provides real-time frame rates and outperforms the CPU-based implementation. When the number of slices is not sufficient, we add in-between slices computed by interpolation. This improves then the quality of the rendered images. We have also implemented the ray marching algorithm on the GPU. The results generated by the three algorithms (CPU-based and GPU-based Shear- Warp, GPU-based Ray Marching) for two test models has proved that the ray marching algorithm outperforms the shear-warp methods in terms of speed up and image quality.

Keywords: Volume rendering, graphics processors

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Authors: S. G. Yasreen, N. B. Madzlan, K. Ibrahim

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Fatigue cracking continues to be the main challenges in improving the performance of bituminous mixture pavements. The purpose of this paper is to look at some aspects of the effects of fine aggregate properties on the fatigue behaviour of hot mixture asphalt. Two types of sand (quarry and mining sand) with two conventional bitumen (PEN 50/60 & PEN 80/100) and four polymers modified bitumen PMB (PM1_82, PM1_76, PM2_82 and PM2_76) were used. Physical, chemical and mechanical tests were performed on the sands to determine their effect when incorporated with a bituminous mixture. According to the beam fatigue results, quarry sand that has more angularity, rougher, higher shear strength and a higher percentage of Aluminium oxide presented higher resistance to fatigue. Also a PMB mixture gives better fatigue results than conventional mixtures, this is due to the PMB having better viscosity property than that of the conventional bitumen.

Keywords: Beam fatigue test, chemical property, mechanical property, physical property

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Authors: Neela. R. Rayavarapu, Neelam Rup Prakash

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The paper discusses a computationally efficient method for the design of prototype filters required for the implementation of an M-band cosine modulated filter bank. The prototype filter is formulated as an optimum interpolated FIR filter. The optimum interpolation factor requiring minimum number of multipliers is used. The model filter as well as the image suppressor will be designed using the Kaiser window. The method will seek to optimize a single parameter namely cutoff frequency to minimize the distortion in the overlapping passband.

Keywords: Cosine modulated filter bank, interpolated FIR filter, optimum interpolation factor, prototype filter.

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Authors: Rahim Sotoudeh Bahreini, Alireza Foroughi Nematollahi, Akbar Jafari

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This study investigates the mechanism of a Gyratory crusher-located in Golgohar mining and industrial Co. specifically with a focus on stresses distribution and fatigue failure of its main shaft. At first step, the cross section of the fractured shaft is studied, and the crack growth is analyzed. Then, the rotational motion of the shaft and the oil temperature of oil circuit of equipment are monitored. Condition monitoring is used to help finding a better modification. Based on the results of this study, the main causes of shaft failure are identified, and corrective solution is offered to increase crusher performance, especially its main shaft life. To predict the efficiency of the proposed modification, finite element simulation is performed, and its results are compared with the similar modified cases. The comparison and interpretation of simulation results confirm the efficiency of proposed corrective method.

Keywords: Fatigue failure, finite element method, gyratory crusher, condition monitoring.

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Authors: Guezouli Larbi, Belkacem Soundes

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The automation of the text detection process can help the human in his driving task. Its application can be very useful to help drivers to have more information about their environment by facilitating the reading of road signs such as directional signs, events, stores, etc. In this paper, a system consisting of two stages has been proposed. In the first one, we used pseudo-Zernike moments to pinpoint areas of the image that may contain text. The architecture of this part is based on three main steps, region of interest (ROI) detection, text localization, and non-text region filtering. Then, in the second step, we present a convolutional neural network architecture (On-Road Text Detection Network - ORTDN) which is considered as a classification phase. The results show that the proposed framework achieved ≈ 35 fps and an mAP of ≈ 90%, thus a low computational time with competitive accuracy.

Keywords: Text detection, CNN, PZM, deep learning.

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Authors: Ibrahim A. El rube, Mohamed T. El Sonni, Soha S. Saleh

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the cursive nature of the Arabic writing makes it difficult to accurately segment characters or even deal with the whole word efficiently. Therefore, in this paper, a printed Arabic sub-word recognition system is proposed. The suggested algorithm utilizes geometrical moments as descriptors for the separated sub-words. Three types of moments are investigated and applied to the printed sub-word images after dividing each image into multiple parts using windowing. Since moments are global descriptors, the windowing mechanism allows the moments to be applied to local regions of the sub-word. The local-global mixture of the proposed scheme increases the discrimination power of the moments while keeping the simplicity and ease of use of moments.

Keywords: Arabic sub-word recognition, windowing, aspectratio, moments.

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Authors: Mario Mastriani

Abstract:

We describe a new filtering approach in the wavelet domain for image denoising and compression, based on the projections of details subbands coefficients (resultants of the splitting procedure, typical in wavelet domain) onto the approximation subband coefficients (much less noisy). The new algorithm is called Projection Onto Approximation Coefficients (POAC). As a result of this approach, only the approximation subband coefficients and three scalars are stored and/or transmitted to the channel. Besides, with the elimination of the details subbands coefficients, we obtain a bigger compression rate. Experimental results demonstrate that our approach compares favorably to more typical methods of denoising and compression in wavelet domain.

Keywords: Compression, denoising, projections, wavelets.

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Authors: Aissa Saoudi, Hassane Essafi

Abstract:

In this work we will present a new approach for shot transition auto-detection. Our approach is based on the analysis of Spatio-Temporal Video Slice (STVS) edges extracted from videos. The proposed approach is capable to efficiently detect both abrupt shot transitions 'cuts' and gradual ones such as fade-in, fade-out and dissolve. Compared to other techniques, our method is distinguished by its high level of precision and speed. Those performances are obtained due to minimizing the problem of the boundary shot detection to a simple 2D image partitioning problem.

Keywords: Boundary shot detection, Shot transition detection, Video analysis, Video indexing.

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Authors: A. Harifi, A. Aghagolzadeh

Abstract:

The main problem for recognition of handwritten Persian digits using Neural Network is to extract an appropriate feature vector from image matrix. In this research an asymmetrical segmentation pattern is proposed to obtain the feature vector. This pattern can be adjusted as an optimum model thanks to its one degree of freedom as a control point. Since any chosen algorithm depends on digit identity, a Neural Network is used to prevail over this dependence. Inputs of this Network are the moment of inertia and the center of gravity which do not depend on digit identity. Recognizing the digit is carried out using another Neural Network. Simulation results indicate the high recognition rate of 97.6% for new introduced pattern in comparison to the previous models for recognition of digits.

Keywords: Pattern recognition, Persian digits, NeuralNetwork.

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Authors: Francesco Maiorana

Abstract:

In this paper a one-dimension Self Organizing Map algorithm (SOM) to perform feature selection is presented. The algorithm is based on a first classification of the input dataset on a similarity space. From this classification for each class a set of positive and negative features is computed. This set of features is selected as result of the procedure. The procedure is evaluated on an in-house dataset from a Knowledge Discovery from Text (KDT) application and on a set of publicly available datasets used in international feature selection competitions. These datasets come from KDT applications, drug discovery as well as other applications. The knowledge of the correct classification available for the training and validation datasets is used to optimize the parameters for positive and negative feature extractions. The process becomes feasible for large and sparse datasets, as the ones obtained in KDT applications, by using both compression techniques to store the similarity matrix and speed up techniques of the Kohonen algorithm that take advantage of the sparsity of the input matrix. These improvements make it feasible, by using the grid, the application of the methodology to massive datasets.

Keywords: Clustering algorithm, Data mining, Feature selection, Grid, Kohonen Self Organizing Map.

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinié

Abstract:

Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. In this context, the automation of this task is urgent. In this work, we compare classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN and Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches.

Keywords: Image segmentation, stuck particles separation, Sobel operator, thresholding.

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Authors: R. Blythman, N. Jeffers, T. Persoons, D. B. Murray

Abstract:

The exploitation of flow pulsation in micro- and mini-channels is a potentially useful technique for enhancing cooling of high-end photonics and electronics systems. It is thought that pulsation alters the thickness of the hydrodynamic and thermal boundary layers, and hence affects the overall thermal resistance of the heat sink. Although the fluid mechanics and heat transfer are inextricably linked, it can be useful to decouple the parameters to better understand the mechanisms underlying any heat transfer enhancement. Using two-dimensional, two-component particle image velocimetry, the current work intends to characterize the heat transfer mechanisms in pulsating flow with a mean Reynolds number of 48 by experimentally quantifying the hydrodynamics of a generic liquid-cooled channel geometry. Flows circulated through the test section by a gear pump are modulated using a controller to achieve sinusoidal flow pulsations with Womersley numbers of 7.45 and 2.36 and an amplitude ratio of 0.75. It is found that the transient characteristics of the measured velocity profiles are dependent on the speed of oscillation, in accordance with the analytical solution for flow in a rectangular channel. A large velocity overshoot is observed close to the wall at high frequencies, resulting from the interaction of near-wall viscous stresses and inertial effects of the main fluid body. The steep velocity gradients at the wall are indicative of augmented heat transfer, although the local flow reversal may reduce the upstream temperature difference in heat transfer applications. While unsteady effects remain evident at the lower frequency, the annular effect subsides and retreats from the wall. The shear rate at the wall is increased during the accelerating half-cycle and decreased during deceleration compared to steady flow, suggesting that the flow may experience both enhanced and diminished heat transfer during a single period. Hence, the thickness of the hydrodynamic boundary layer is reduced for positively moving flow during one half of the pulsation cycle at the investigated frequencies. It is expected that the size of the thermal boundary layer is similarly reduced during the cycle, leading to intervals of heat transfer enhancement.

Keywords: Heat transfer enhancement, particle image velocimetry, localized and time-resolved velocity, photonics and electronics cooling, pulsating flow, Richardson’s annular effect.

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Authors: Khairullah Khan, Baharum B. Baharudin, Aurangzeb Khan, Fazal_e_Malik

Abstract:

Opinion extraction about products from customer reviews is becoming an interesting area of research. Customer reviews about products are nowadays available from blogs and review sites. Also tools are being developed for extraction of opinion from these reviews to help the user as well merchants to track the most suitable choice of product. Therefore efficient method and techniques are needed to extract opinions from review and blogs. As reviews of products mostly contains discussion about the features, functions and services, therefore, efficient techniques are required to extract user comments about the desired features, functions and services. In this paper we have proposed a novel idea to find features of product from user review in an efficient way. Our focus in this paper is to get the features and opinion-oriented words about products from text through auxiliary verbs (AV) {is, was, are, were, has, have, had}. From the results of our experiments we found that 82% of features and 85% of opinion-oriented sentences include AVs. Thus these AVs are good indicators of features and opinion orientation in customer reviews.

Keywords: Classification, Customer Reviews, Helping Verbs, Opinion Mining.

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Authors: Phumelele P. Kubheka, Pius A. Owolawi, Gbolahan Aiyetoro

Abstract:

Twitter is one of the most popular social media platforms where users share their opinions on different subjects. Twitter can be considered a great source for mining text due to the high volumes of data generated through the platform daily. Many industries such as telecommunication companies can leverage the availability of Twitter data to better understand their markets and make an appropriate business decision. This study performs topic modeling on Twitter data using Latent Dirichlet Allocation (LDA). The obtained results are benchmarked with another topic modeling technique, Latent Semantic Indexing (LSI). The study aims to retrieve topics on a Twitter dataset containing user tweets on South African Telcos. Results from this study show that LSI is much faster than LDA. However, LDA yields better results with higher topic coherence by 8% for the best-performing model in this experiment. A higher topic coherence score indicates better performance of the model.

Keywords: Big data, latent Dirichlet allocation, latent semantic indexing, Telco, topic modeling, Twitter.

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