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Hierarchical Contaminated Web Page Classification Based on Meta Tag Denoising Disposal
<span title="2021-11-16">2021</span>
<i title="Hindawi Limited">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/sdme5pnua5auzcsjgqmqefb66m" style="color: black;">Security and Communication Networks</a>
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We choose the top-down method for hierarchical classification to improve the prediction efficiency. ...
Web page classification is critical for information retrieval. ...
To solve the problem of classification efficiency, this paper proposed a web page classification method based on meta tag text such as the Title and the Description. ...
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DL-PER: Deep Learning Model for Chinese Prehospital Emergency Record Classification
<span title="">2022</span>
<i title="Institute of Electrical and Electronics Engineers (IEEE)">
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A weighted text convolutional neural network (WTextCNN) improves this model's local text feature extraction capability. ...
Then, we use a bidirectional long and short-term memory (BiLSTM) model to obtain text features from a global perspective. ...
It may be because BiLSTM has difficulty extracting local text features from deep levels. ...
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Efficient Sentimental Analysis Using Ensemble Learning for Big Data
<span title="2022-05-31">2022</span>
<i title="International Journal for Research in Applied Science and Engineering Technology (IJRASET)">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hsp44774azcezeyiq4kuzpfh5a" style="color: black;">International Journal for Research in Applied Science and Engineering Technology</a>
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To make model suitable for real world and to handle big data, the model is deployed on Apache Spark. ...
In this work, a sentiment prediction model for standford and Amazon data is proposed. The proposed model utilizes ensemble learning and clustering approaches for sentiment prediction. ...
[11] proposed a new sentiment-based meta-level features for effective sentiment analysis. ...
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Arabic Sentiment Analysis with Optimal Combination of Features Selection and Machine Learning Approaches
<span title="2016-09-05">2016</span>
<i title="Maxwell Scientific Publication Corp.">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/itifugluyrhulokjxf64yqrfey" style="color: black;">Research Journal of Applied Sciences Engineering and Technology</a>
</i>
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Most of the research work on sentiment analysis was focused on the texts in the English language. ...
the N-gram model and the Meta-classifier approach) for the implementation of sentiment classification in the Arabic language. ...
The selection process brings positive effects, improving the scalability, efficiency and accuracy of the text classifier. ...
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A Study on Anthropomorphic Animal Characters Search System Visualization for UX Design
<span title="2014-12-30">2014</span>
<i title="Korea Multimedia Society">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/qh6pwvxgsvfjtgydwmknbgobiy" style="color: black;">Journal of Korea Multimedia Society</a>
</i>
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To this end, meta data were utilized herein to elevate the search efficiency of multimedia information and text information. ...
This paper presents to design User eXperience(UX) of anthropomorphic animal characters search system (hereinafter, AACSS) for efficient user search. ...
Through the mammalian classification, it is designed for a user to easily realize the position of each animal on the animal classification system. ...
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Exploiting New Sentiment-Based Meta-level Features for Effective Sentiment Analysis
<span title="">2016</span>
<i title="ACM Press">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/puezkhxc3rggrgb456avsvxi34" style="color: black;">Proceedings of the Ninth ACM International Conference on Web Search and Data Mining - WSDM '16</a>
</i>
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representation (by up to 16%) but is also superior in most cases to state-ofart meta-level features previously proposed in the literature for text classification tasks that do not take into account some ...
Experiments performed with a substantial number of datasets (nineteen) demonstrate that the effectiveness of the proposed sentiment-based meta-level features is not only superior to the traditional bag-of-word ...
Meta-Level Features for Text Classification Meta-features have been proposed to improve the effectiveness of text classification. ...
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Hybrid Model using Stack-Based Ensemble Classifier and Dictionary Classifier to Improve Classification Accuracy of Twitter Sentiment Analysis
<span title="2020-07-25">2020</span>
<i title="The World Academy of Research in Science and Engineering">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/l2ghh6vzxbh45awjxwipefhnue" style="color: black;">International Journal of Emerging Trends in Engineering Research</a>
</i>
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implemented on this enhanced feature set. ...
In the present research, a hybrid model based on stack based ensemble classifiers and dictionary based classifier is used for tweet classification as positive and negative. ...
Ensemble is performed at two levels one at feature selection level and other at classifier level. ...
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A Novel Multi-View Ensemble Learning Architecture to Improve the Structured Text Classification
<span title="2022-06-01">2022</span>
<i title="MDPI AG">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dmr4kpn2yreovpdxpdiqtjcrnu" style="color: black;">Information</a>
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To test its efficiency for full text classification, a technique has been implemented where the views correspond to the document sections. ...
For classification and prediction, we use a stacking generalization based on the idea that different learning algorithms provide complementary explanations of the data. ...
To test its efficiency for full text classification, in this work, a novel stacking technique where the views correspond to the document sections is proposed. ...
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Ensemble of feature sets and classification algorithms for sentiment classification
<span title="2011-03-15">2011</span>
<i title="Elsevier BV">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ozlq63ehnjeqxf6cuxxn27cqra" style="color: black;">Information Sciences</a>
</i>
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Second, three well-known text classification algorithms, namely naï ve Bayes, maximum entropy and support vector machines, are employed as base-classifiers for each of the feature sets. ...
In this paper, we make a comparative study of the effectiveness of ensemble technique for sentiment classification. ...
Introduction Text classification has been one of the key tools to automatically handle and organize text information for decades. ...
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Generating Concept Hierarchies from Text for Intelligence Analysis
[chapter]
<span title="">2004</span>
<i title="Springer Berlin Heidelberg">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a>
</i>
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Other research on texts focuses on classifying the whole text into categories. However, texts might be diverse in subjects and suffer from classification accuracy. ...
It is important to automatically extract key information from sensitive text documents for intelligence analysis. ...
The feature vectors obtained are used for both class model creation and concept classification. ...
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Multi-View Learning for Web Spam Detection
[article]
<span title="2013-07-24">2013</span>
<i >
arXiv
</i>
<span class="release-stage" >pre-print</span>
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<span title="2013-05-16">2013</span> <span class="release-stage" >pre-print</span> <span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1305.3814v1">arXiv:1305.3814v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vn5tlcrvhrgnxihrtfazfd3s6q">fatcat:vn5tlcrvhrgnxihrtfazfd3s6q</a> </span>
Therefore, spam pages should be removed using an effective and efficient spam detection system. ...
Previous methods for web spam classification used several features from various information sources (page contents, web graph, access logs, etc.) to detect web spam. ...
They also wish to thank Hadi Sharifi, Amin Nikookaran, and Ali Shirvani for their collaboration. ...
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<a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1305.3814v2">arXiv:1305.3814v2</a>
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Assessing the Influence Level of Food Safety Public Opinion with Unbalanced Samples Using Ensemble Machine Learning
<span title="2022-02-14">2022</span>
<i title="Hindawi Limited">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/fw4azkpu65d2thmrwfkoawyxse" style="color: black;">Scientific Programming</a>
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In this paper, we model the assessment of public opinion influence as a text classification task. ...
Assessing the public opinion on food safety events constitutes an important job of government regulators. ...
Text Classification for Public Opinion Assessment. Text classification plays an important role in public opinion assessment. ...
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Adaptive Region Embedding for Text Classification
<span title="2019-07-17">2019</span>
<i title="Association for the Advancement of Artificial Intelligence (AAAI)">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wtjcymhabjantmdtuptkk62mlq" style="color: black;">PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE</a>
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We extensively evaluate our method on 8 benchmark datasets for text classification. ...
Deep learning models such as convolutional neural networks and recurrent networks are widely applied in text classification. ...
We also thank reviewers for their constructive comments. ...
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<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1609/aaai.v33i01.33017314">doi:10.1609/aaai.v33i01.33017314</a>
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Visual information retrieval from large distributed online repositories
<span title="1997-12-01">1997</span>
<i title="Association for Computing Machinery (ACM)">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/i6iajiiyxvgz3ob6jwcn2pufni" style="color: black;">Communications of the ACM</a>
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With the tremendous amount of visual information becoming on-line, how does one find visual information from distributed repositories efficiently, at least to the same extent as that of existing information ...
We will discuss the role of contentbased visual query, present a taxonomy for classifying existing VIRS, present a working Internet VIRS as a case study, describe a preliminary prototype of Internet meta ...
Meta Search Engines for Images The proliferation of text search engines on the Web has motivated recent research in "integrated search" or so called "meta search engines". ...
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<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/265563.265573">doi:10.1145/265563.265573</a>
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Survey Paper on Algorithms used for Sentiment Analysis
<span title="2020-05-31">2020</span>
<i title="International Journal for Research in Applied Science and Engineering Technology (IJRASET)">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hsp44774azcezeyiq4kuzpfh5a" style="color: black;">International Journal for Research in Applied Science and Engineering Technology</a>
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Our paper also focuses on the three kinds of machine learning algorithms for Sentiment Analysis-Supervised, Unsupervised and Semi-Supervised Machine Learning Algorithms. I. ...
The topics henceforth explored include various algorithms, quality measurement metrics, feature selection and training methods. ...
gain and chooses the one that selects best features for efficient classification. ...
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<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.22214/ijraset.2020.5089">doi:10.22214/ijraset.2020.5089</a>
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