[PDF] Top 20 Research and Application of Improved K means Algorithm in Text Clustering
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Research and Application of Improved K means Algorithm in Text Clustering
... massive text information has become the focus of the current research on computer information ...theory[1-2]. Clustering, as an important branch of data mining, has a wide range of ...methods, ... See full document
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ARABIC TEXT CLUSTERING BASED ON K MEANS ALGORITHM WITH SEMANTIC WORD EMBEDDING
... This research aims to provide information about the design of an evaluation model that is suitable to be used to evaluate the level of effectiveness of the application of e-learning in health colleges in ... See full document
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ARABIC TEXT CLUSTERING BASED ON K MEANS ALGORITHM WITH SEMANTIC WORD EMBEDDING
... software application is highly recommended in the real-time ...subspace clustering approach using evolutionary computation based optimal solution identification for dimension ... See full document
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ARABIC TEXT CLUSTERING BASED ON K MEANS ALGORITHM WITH SEMANTIC WORD EMBEDDING
... Conventional wireless communication systems consider packet collisions as a problem and try to avoid them by using techniques like channel reservations, carrier sense, or arbitrated medium access (TDMA, polling). The ... See full document
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ARABIC TEXT CLUSTERING BASED ON K MEANS ALGORITHM WITH SEMANTIC WORD EMBEDDING
... Based on the study that we have done, we conclude that Linear regression models have been used in regions with minimum congestion numbers. The model uses a traffic pattern that is very similar to the previous traffic ... See full document
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ARABIC TEXT CLUSTERING BASED ON K MEANS ALGORITHM WITH SEMANTIC WORD EMBEDDING
... Recently, Arabic Natural Language Processing (ANLP) gained the attention of many researchers in the era of information explosion especially with the tremendous amount of Arabic internet users who resulted in the rapid ... See full document
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Clustering Behavioral Data for Advertising Purposes using K Prototypes Algorithm
... or clustering them according to their interests and ...the k-prototypes clustering algorithm, which is an improved combination of k-means and k-modes ... See full document
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ARABIC TEXT CLUSTERING BASED ON K MEANS ALGORITHM WITH SEMANTIC WORD EMBEDDING
... The proposal of a new theoretically sound conceptual model of academic performance factors in the e-Learning context is the main innovation of this study compared to the four above presented reviews, in addition to the ... See full document
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ARABIC TEXT CLUSTERING BASED ON K MEANS ALGORITHM WITH SEMANTIC WORD EMBEDDING
... pooling improved detection accuracy for object detection with scale-specific branches attached convolutional layers and the layer-wise cascaded rejection classifiers speeded up the ... See full document
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Improved Innovative Center Using K-means Clustering Algorithm and EFCA
... commercial application is huge where the number of records in a dataset can vary from some thousand to thousand of millions ...Basically, clustering is justify as a process used for grouping a large number ... See full document
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ARABIC TEXT CLUSTERING BASED ON K MEANS ALGORITHM WITH SEMANTIC WORD EMBEDDING
... each application such that the total system utility is maximized under the constraints that every application is feasible with respect to each QoS ...all application utility. Hence [35] proposed a ... See full document
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ARABIC TEXT CLUSTERING BASED ON K MEANS ALGORITHM WITH SEMANTIC WORD EMBEDDING
... 2912 the current research[28] . Despite the model’s potential to explain the behavioural intention towards adoption of technology and its usage, it was originally focused onto large-sized organization use. It was ... See full document
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A Framework for Outlier Detection Using Improved Bisecting k-Means Clustering Algorithm
... based, k-Nearest neighbor ...based algorithm and the distance based algorithm are merged ...[12]. Clustering is one of the most important techniques used in data mining to find interesting ... See full document
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Application of Factor Analysis to k means Clustering Algorithm on Transportation Data
... Travel Demand Models are employed in decision making process of large infrastructure projects in Metropolitan cities. In this process, a number of traffic and transportation studies are conducted. Among them, the most ... See full document
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Medical Image Segmentation using Modified K Means Clustering
... major research topic for many image processing ...etc. Clustering is the search for distinct groups in the feature ...The clustering task separates the data into number of partitions, which are ... See full document
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Plant Operation Working Condition of the Optimal Combination of External Research Division
... An improved K-means algorithm is proposed to solve the problem of load and coal quality characteristics, overcome the traditional K-means algorithm to set the initial ... See full document
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ARABIC TEXT CLUSTERING BASED ON K MEANS ALGORITHM WITH SEMANTIC WORD EMBEDDING
... Many research has been done using evolutionary algorithms for victim ...Competitive Algorithm (RDICA) algorithm has been used for victim localization, to avoid a local optima problem, the exploration ... See full document
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Clustering based information retrieval with the aco and the k-means clustering algorithm
... emerging research field which allows the user to retrieve the required information from the ...data clustering and the feature selection ...finds application in the various research fields, ... See full document
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ARABIC TEXT CLUSTERING BASED ON K MEANS ALGORITHM WITH SEMANTIC WORD EMBEDDING
... Besides giving the training in the ability to analyze and calculate with some browsing methods, probability and certainty level, artificial neural network can think and adaptate with one problem both to controlled and ... See full document
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Application of Modified K Means Clustering Algorithm in Segmentation of Medical Images of Brain Tumor
... Segmentation of an image is a major research topic for many researchers involved in the field of image processing. There are obvious reasons and endless applications in the field of computer vision and analysis of ... See full document
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