large text classification problem
A Survey on Text Classification with Different Types of Classification Methods
... Text Classification is an important application area in information retrieval, text mining and machine learning why because classifying millions of text document manually is an expensive and ...
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Sparse Victory – A Large Scale Systematic Comparison of count-based and prediction-based vectorizers for text classification
... Tables 2 and 5, illustrate the performance of vectorizers and classifiers for all datasets whose size is less than 10K. The results have been grouped on a per category basis, in the category column the number inside the ...
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Semi Supervised Learning with Auxiliary Evaluation Component for Large Scale e Commerce Text Classification
... the problem of label quality is one of the active areas of active learning ...the problem of active learning where labels were obtained from strong and weak ...the problem where they have extra ...
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DATA MINING AND TEXT MINING: EFFICIENT TEXT CLASSIFICATION USING SVMS FOR LARGE DATASETS Srikanth Bethu*, B Sankara Babu
... dual problem will give better solution and also to be observed is that, for all the cases, we have not worked with the complete (whole) dataset at one time at ...
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On the use of text classification methods for text summarisation
... semi-automated classification technique called SARSET (Semi-Automated Rule Summarisation Extraction Tool) which was aimed at conduct- ing document summarisation classification by providing a mechanism for ...
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Multi Dimensional Text Classification
... affect classification accuracy of multi- dimensional category model: training set size and the granularity of ...flat-based classification in the multi-dimensional model deals with the finest granularity of ...
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How Large a Vocabulary Does Text Classification Need? A Variational Approach to Vocabulary Selection
... Vocabulary Reduction An orthogonal line of research for dealing similar vocabulary redun- dancy problem is the character-based approaches to reduce vocabulary sise (Kim et al., 2016; Zhang et al., 2015; ...
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Large-scale Multi-Label Text Classification for an Online News Monitoring System
... various classification tasks, it is also necessary to briefly in- troduce the field of natural language processing (NLP) in order to (a) outline the target setting for which this research and its associated ...
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Manipulating Large Corpora for Text Classification
... the problem of dealing with a large collection of data and report on an em- pirical study for text classification which manipu- lates data using two well-known machine learning techniques, ...
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Text Categorization as a Graph Classification Problem
... Gaston (Nijssen and Kok, 2004). The number of frequent subgraphs can be enormous, especially for large graph collections, and handling such a feature set can be very expensive. To overcome this issue, recent works ...
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Text Level Graph Neural Network for Text Classification
... on text clas- sification, since GNN does well in handling complex structures and preserving global in- ...input text with global parameters sharing instead of a single graph for the whole ...ual text ...
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Large Scale Energy Management Problem
... A large-scale energy management problem with varied ...a large variety of factors, this leads to the need of multiple uncertainty ...examined problem comprises three fields of optimization: ...
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Granular Space and the Problem of Large Numbers
... this universality were searched for, the problem of the standards of length, mass and time appeared. These standards were to be established from the principles not appealing to any substance including elementary ...
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REVIEW ON TEXT CLASSIFICATION USING DIFFERENT CLASSIFICATION TECHNIQUES
... proper classification of large amount of information present over the internet is very critical step towards the business due to the explosive growth of the textual information day by day from the ...
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Weakly-supervised text classification
... text classification. Despite the success of deep neural models in flat text classification and their advantages over traditional classifiers, applying them to hierarchical text ...
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Automatic Arabic Text Classification
... document classification is an important text mining task especially with the rapid growth of the number of online documents present in Arabic ...language. Text classification aims to ...
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Semi-Automated Text Classification
... of classification between different scenarios of annotation, ...The problem is approached by ranking documents according to the probabilistic outputs of a ...
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Active Learning for Text Classification
... algorithm (Blum & Mitchell, 1998) which assumes that each example has two con- ditionally independent feature divisions. Then two separate classifiers can be build from the two feature divisions. Examples which can ...
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Surname typology and the problem of inconsistent classification
... and classification of ...name classification” can be rejected, as all chi-squared values are above the critical value of ...name classification, is less than ...
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Text Classification and Classifiers: A Comparative Study
... Support Vector Machine (SVM), is one of most efficient machine learning algorithm. The original SVM algorithm was invented by Vladimir N. Vapnik and Alexey Ya. Chervonenkis in 1963 and used mostly for pattern ...
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