Term-weighting
Reducing Over Weighting in Supervised Term Weighting for Sentiment Analysis
... supervised term weighing scheme, introduced by Martineau and Finin (2009), is called delta ...as term weights, the authors assigned term weights for a document by calculating the difference of that ...
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The Use of Dependency Relation Graph to Enhance the Term Weighting in Question Retrieval
... the term weighting- based question retrieval models is that they overlook the relations between term pairs when computing their ...novel term weighting scheme by incorporating the ...
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Term Weighting Based on Index of Genre for Web Page Genre Classification
... of weighting is the document-based ...the term appearing often in a genre should be more significant in document indexing compared to the term appearing frequently in many genres despites its high ...
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Influence of functional words, term weighting measures and classifiers on Text classification
... various term weighting ...different term weighting schemes such as Term frequency, TF-IDF, TF-RF, TF- CHI- SQUARED with an assumption that the term frequency is a good factor for ...
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A Novel Text Classifier Using Supervised and Unsupervised Term Weighting Method
... of term weighting methods specially unsupervised term weighting methods has close relationship with learning algorithms and data corpora and we can also state that ...use term ...
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Data mining, Text categorization, Term weighting, Vector space model.
... In this paper, we investigated different variations of VSM using KNN algorithm, these variations are: Cosine coefficient, Jacaard coefficient and Dice coefficient, using IDF and WIDF term weighting ...
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Classification of Online Grooming on Chat Logs Using Two Term Weighting Schemes
... two term weighting schemes on two datasets are used to improve the content-based classification ...two term weighting schemes in classifying grooming contents. Two term weighting ...
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Preference Based Term Weighting for Arabic Fiqh Document Ranking
... erence Frequency with α value (IPF α ). The IPF function assigns the lowest score to those terms that appear in multiple candidate user preference. Constant α is a multiplier that will increase the weights according to ...
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An Approach for Optimal Feature Subset Selection using a New Term Weighting Scheme and Mutual Information
... feature weighting to extract the features using a different term weighting approach for content, URL, heading, title, anchor text and information present in the ...
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PubMed-supported clinical term weighting approach for improving inter-patient similarity measure in diagnosis prediction
... novel weighting approaches, namely generic term weighting and specific term weighting, are proposed to improve the performance of the onto- logical vector model in predicting ...
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Short Text Classification Using An Enhanced Term Weighting Scheme And Filter-Wrapper Feature Selection
... proposed term weighting scheme and compare it with a set of common term weighting ...combination weighting scheme and all introduced feature selection methods and their capability to ...
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Classification of terrorism based on tweet text post on twitter using term weighting schemes
... three term weighting schemes on two datasets are used to improve the automated content-based classification techniques, which is required to filter out unwanted ...
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Term Weighting Based on Positive Impact Factor Query for Arabic Fiqh Document Ranking
... key term. Key term is a word that has higher information and value than the others in ...key term in term weighting process could led to an improvement on result’s ...in term ...
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A Supervised Term-Weighting Method and its Application to Variable Extraction from Digital Media
... Abstract. Successful modeling and prediction depend on effective methods for the extraction of domain-relevant variables. This paper proposes a methodology for identifying domain-specific terms. The proposed methodology ...
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A Flexible Supervised Term-Weighting Technique and its Application to Variable Extraction and Information Retrieval
... Successful modeling and prediction depend on effective methods for the extraction of domain-relevant variables. This paper proposes a methodology for identifying domain-specific terms. The proposed methodology relies on ...
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Opinion Mining and Topic Categorization with Novel Term Weighting
... novel term weighting algorithm for opin- ion mining and topic categorization of arti- cles from newspapers and ...novel term weighting technique with existing approaches such as TF-IDF and ...
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Improved Term Weighting Technique for Automatic Web Page Classification
... Good weighting methods are more important than the feature selection process and it is suggested that the two need to go hand-in-hand in order to be ...methods term variance (TV) and docu- ment frequency ...
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Classification of Sexual Harassment on Facebook Using Term Weighting Schemes
... The feature selection methods in this study, namely Entropy, TFIDF and M.TFIDF term weighting schemes. Entropy and M.TFIDF are modifications of TFIDF with a difference that Entropy and M.TFIDF calculates ...
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Learning Term weighting Functions for Similarity Measures
... We split our data into 10 subsets and conducted the experiments using the same 10-fold cross- validation setting described in Sec. 4.1.3, includ- ing how we used the development set to select the regularization ...
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Term Weighting Schemes for Latent Dirichlet Allocation
... as term weighting, which have been com- monplace in LSI for some time (Dumais, 1991), have not yet found a place in ...that weighting is unnecessary in ...idf weighting in both non-reduced ...
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