[PDF] Top 20 Distributional Features for Text Categorization Based on Weight
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Distributional Features for Text Categorization Based on Weight
... on text categorization usually use the appearance or the frequency of appearance to characterize a ...These features are not enough for fully capturing the information contained in a ...using ... See full document
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An Empirical Approach to Text Categorization Based on Term Weight Learning
... The characteristic of our approach is that the degree of con- text dependency is used in order t.o judge whether a word in a text is a true keyword or not.. \Ve applied our technique to [r] ... See full document
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Text Categorization Based on Bayesian Classification Approach using Class-Specific Features
... is measured. One major disadvantage is that using the combination operation may bias the feature importance for discrimination. They built a corpus of slide-paper pairs and used four presentations from it to evaluate ... See full document
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RESEARCH ISSUES IN TEXT CATEGORIZATION BASED ON MACHINE LEARNING: A REVIEW
... decision based on events and their expected outcomes ...system based on decision tree and symbolic rule for text ...including text categorization for a long ...For text ... See full document
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Improving the Operation of Text Categorization Systems with Selecting Proper Features Based on PSO-LA
... the text feature selection methods only aim at auditing the relation and redundancy analysis from the class ...of text classification. During the text classification, words of less importance are ... See full document
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A Survey on Sentiment Based Text Categorization
... The text data is a complex type of data which is not in regular ...normal text data among the size, length, language and the noise is the key issues in text data ...the features of text ... See full document
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Map reduce based bag of phrases representation and distributional features incorporation for text classification
... of features that shall be fed into machine learning algorithms. Features for applying machine learning algorithms to text corpus shall be words, n-grams (phrases) or ...of features in a ... See full document
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Improve Image Categorization based on Novel Features & Weighted Classifier
... requires categorization, by which they can occur effortlessly and in a higher ...simple categorization system consists of a camera fixed high above the interested zone where images are captured and ... See full document
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Auto Text Summarization and Categorization
... Automatic text summarization is to compress the larger original text into shorter text called as ...important features and extracting sentences based on their ...news based URLs ... See full document
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A Novel Fuzzy-Bayesian Classification Method for Automatic Text Categorization
... Text categorization is mostly required to label the documents automatically with the predefined set of ...automatic text categorization using the class-specific ...class features are ... See full document
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Distributional Word Clusters vs. Words for Text Categorization (Kernel Machines Section)
... multi-labeled categorization results obtained by the two categorization schemes (BOW+MI and IB) over Reuters (10 largest categories) and 20NG ...labeled categorization of this ...multi-labeled ... See full document
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Chinese Short Text Categorization Based on Semi Supervised Learning
... in text classification, image recognition and other fields [11]. The text categorization algorithm which is based on boosting was proposed by RE Schapire and Y Singer [12], which laid a ... See full document
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Exploiting Domain Knowledge via Grouped Weight Sharing with Application to Text Categorization
... stochastic weight sharing. We have showed it generally improves text classification performance ...approach based on retrofitting prior to ...inform weight sharing using other varieties and ... See full document
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Occam’s razor-based spam filter
... in text categorization, like rule induction algorithm [20,21], Rocchio [31,43,10], Boosting [19,40], decision tree [48], memory-based learning [12], Naïve Bayes (NB) classifiers [42,11,50,46,3,5,7] ... See full document
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Text Categorization for Authorship based on the Features of Lingual Conceptual Expression
... The text categorization is an important field for the automatic text information ...a text can be treated as a special text ...expression based on the Hierarchical Network of ... See full document
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WEIGHTING INDIVIDUAL OPTIMAL FEATURE SELECTION IN NAIVE BAYES FOR TEXT CLASSIFICATION
... 378 | P a g e That time features selection is necessary. May hurts prognosticative performance of classification in text categorization. A common approach of feature reduction is to introduce those ... See full document
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Latin Etymologies as Features on BNC Text Categorization
... discriminative features beyond words/phrases frequencies based on linguistic analysis and have not been reached yet up to now and limit the efficient features set as small as it can ...available ... See full document
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Query Translation by Text Categorization
... served that cosine normalization was especially effective for our task. This is not surprising, considering the fact that cosine normalization performs well when documents have a similar length (Singhal et al., 1996). As ... See full document
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Oceanographic Big Data Text Categorization Algorithm Based on Improved Mutual Information
... Text categorization [1] refers to use computer programs and related algorithms for allocating the target text to the category by comparing the contents of the target texts and training ...the ... See full document
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A Comparison and Semi Quantitative Analysis of Words and Character Bigrams as Features in Chinese Text Categorization
... There are also differences in some other as- pects of IR and TC. So it is significant to make a detailed comparison and analysis here on the relative value of words and bigrams as features in Text ... See full document
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