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Using Virtual Examples for Text Classification with Support Vector Machines
サポートベクタマシンを使った文書分類における仮想事例の利用
2006
Journal of Natural Language Processing
サポートベクタマシンを使った文書分類における仮想事例の利用
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We explore how virtual examples(artificially created examples)improve performance of text classification with Support Vector Machines(SVMs).We propose techniques to create virtual examples for text classification ...
We evaluate the proposed methods by Reuters-21758 test set collection.Experimental results show virtual examples improve the performance of text classification with SVMs,especially for small training sets ...
Text
Categorization with Support Vector Machines: Learning with
Many Relevant Features." In Proceedings of the 10th European Conference on Machine
Learning, pp.137-142.
Joachims, T.(1999)." ...
doi:10.5715/jnlp.13.3_21
fatcat:zibv2c2xujgrfiemzpukdenvzi
TREC 11 Experiments at NII: The Effects of Virtual Relevant Documents in Batch Filtering
2002
Text Retrieval Conference
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Researches on document retrieval, text categorization and routing have shown the effects of learning by sampling relevant documents or non-relevant document from training set. ...
Support Vectors Given training documents which include not only training documents but also VRDs, we have used support vector machine (Vapnik, 1995)
Experiments
Experimental Procedure In the runs ...
dblp:conf/trec/LeeKA02
fatcat:rlw5wvpsgncuja5rqh5l4dp6ry
A multilingual text mining approach to web cross-lingual text retrieval
2004
Knowledge-Based Systems
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Second, the multilingual concept -term relationships, in turn, are used to discover the conceptual content of the multilingual text, which is either a document containing potentially relevant information ...
data relevant to a domain. ...
In our multilingual text categorization problem, the nearest neighbor to an unclassified text with k index terms will be the k single-term virtual documents where each of them contains one of the unclassified ...
doi:10.1016/j.knosys.2004.04.001
fatcat:xcvrtmnhkve67eauw6ohzjpky4
Construction of supervised and unsupervised learning systems for multilingual text categorization
2009
Expert systems with applications
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We selected support vector machines (SVM) as representative of supervised techniques as well as latent semantic indexing (LSI) and self-organizing maps (SOM) techniques as our selective ones of unsupervised ...
relevant information, in whatever language and form it may have been stored. ...
Implementation of supervised methods for MTC In our previous work, we employed a supervised text mining technique based on support vector machines (SVMs) for training text classifiers in a combined platform ...
doi:10.1016/j.eswa.2007.12.052
fatcat:rwqnbwz2lra33o4nwvpge6peqi
NewsFinder: Automating an AI News Service
2012
The AI Magazine
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NewsFinder automates the steps involved in finding, selecting, categorizing, and publishing news stories that meet relevance criteria for the Artificial Intelligence community. ...
The software combines a broad search of online news sources with topic-specific trained models and heuristics. ...
Support Vector Machines for Categorization The task of choosing one or more categories for a news story is known as multilabel classification. ...
doi:10.1609/aimag.v33i2.2406
fatcat:ljpvypr6lvg33nuomja6k7zgyq
Empirical Evaluations of Automatic Forum Selector
2012
International Journal of Computer and Communication Engineering
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In this study, we propose the use of text categorization approach to automatically select a target forum category. The empirical evaluations demonstrate the utility of text categorization approach. ...
We also found that decision tree outperformed other machine classifiers. ...
Support Vector Machine consistently improved its performance when more top ranked attributes were added. ...
doi:10.7763/ijcce.2012.v1.16
fatcat:b74drzjo3bclfe5r6zgysxgu6q
Sentence Classification using Machine Learning with Term Frequency–Inverse Document Frequency with N-Gram
[chapter]
2021
New Frontiers in Communication and Intelligent Systems
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The linear support vector machine is most relevant to this work with our proposed model. The final result shows a significant accuracy compared with earlier methods. ...
This paper demonstrates machine learning techniques are used for the text classification process..And also, with the vast rapid growth of text analysis in all areas, the demand for automatic text classification ...
A support vector machine paired with unigrams delivered the best result in their experiments. ...
doi:10.52458/978-81-95502-00-4-35
fatcat:rndrxg6tqncddfscshifzogl24
Machine Learning Algorithms in Web Page Classification
2015
Indian Journal of Science and Technology
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In this paper we tend to use machine learning algorithms like SVM, KNN and GIS to perform a behavior comparison on the net pages classifications drawback, from the experiment we tend to see within the ...
SVM with tiny range of negative documents to make the centroids has the littlest storage demand and also the least on line take a look at computation value. ...
Machine Learning Algorithms
Support Vector Machines (SVM) Support Vector Machine is Associate in Nursing machine learning technique supported applied math Learning theory. ...
doi:10.17485/ijst/2015/v8i31/88974
fatcat:t4ykcxxqrzarnlyimrlyocaxhm
Page 242 of American Society of Civil Engineers. Collected Journals Vol. 16, Issue 4
[page]
2002
American Society of Civil Engineers. Collected Journals
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“Text categorization with support vector machines: learning with many relevant features.” Proc., ECML-98, Springer, Berlin, 137-142.
Joachims, T. (1999). “Making large-scale SVM learning practical.”’ ...
“A probabilistic analysis of the Rocchio algorithm with TFIDF for text categorization.” Proc., ICML-97, Morgan Kauf- mann, San Francisco, 143-151.
Joachims, T. (1998). ...
Fusion Approaches for Mappings between Heterogeneous Ontologies
[chapter]
2001
Lecture Notes in Computer Science
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Text categorization has discussed learning methods to map between full text terms and thesaurus descriptors. ...
Automatic methods for mappings between different ontologies are necessary to ensure successful retrieval of information stored in virtual digital libraries. ...
In recent years neural networks and support vector machines have been employed as well [8, 11] . An overview is provided by Aas and Eikvil [1] . ...
doi:10.1007/3-540-44796-2_8
fatcat:g4ln6lxoa5brhncp6mrvtl7ngu
Novel top-down methods for Hierarchical Text Classification
2011
Procedia Engineering
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We define an virtual subclass for each non-leaf category to help the rejected documents go back to ancestor category ,thus improving the overall performance .Our experiments using Support Vector Machine ...
To classify large-scale text corpora, one common approach is using hierarchical text classification and classifying text documents in a top-down manner. ...
In the literature, many algorithms [1] have been proposed, such as Support Vector Machines (SVM), k-Nearest Neighbor (kNN), Naive Bayes (NB) and so on. ...
doi:10.1016/j.proeng.2011.11.2651
fatcat:yhn4izj3zvfezjf4xbu2zdu4tu
DACS Dewey index-based Arabic Document Categorization System
2012
International Journal of Computer Applications
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Finally a Dewey-Index Based Back-propagation Artificial Neural Network is developed for Arabic Document Categorization. ...
This paper is devoted to the development of Arabic Text Categorization System. First, a stop-words list is generated using statistical approach which captures the inflation of different Arabic words. ...
Text processing tasks: The main goal of this research is to develop a categorization system that start with row text data and ends up with a tagged document with relevant classes. ...
doi:10.5120/7500-0634
fatcat:4fvnz7yqyrhkxb2vfrgksm7324
Optimizing Support Vector Machine Classification Based on Semantic-Text Knowledge Enrichment
2019
Zenodo
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In this research, we enhanced the performance of Support Vector Machine (SVM) in text classification by applying semantic-knowledge enrichment. ...
We propose using semantic-knowledge enrichment scheme to inject new concepts into the original contents of the text documents. ...
Huang, «Support Vector Machines for Text Categorization Based on Latent Semantic Indexing,» 2001. 24. ...
doi:10.5281/zenodo.2576351
fatcat:cvvpr7aeeve6lhkah6uebh5aka
Two Hierarchical Text Categorization Approaches for BioASQ Semantic Indexing Challenge
2013
Conference and Labs of the Evaluation Forum
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This paper describes our participation in the BioASQ semantic indexing challenge with two hierarchical text categorization systems. ...
We describe the adaptations required to deal with a large thesaurus like MeSH and a huge document collection and discuss the results obtained in the BioASQ challenge and the limitations of both approaches ...
Acknowledgements Research reported in this paper has been partially funded by "Ministerio de Economía y Competitividad" and FEDER under the project TIN2010-18552-C03-01, by "Xunta de Galicia" under the ...
dblp:conf/clef/Ribadas-PenaIBR13
fatcat:lkzdp6jbyzhjvae4a3xj3mwchq
Sentiment Analysis Using Machine Learning Approach
2021
Ovidius University Annals: Economic Sciences Series
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The paper proposes a comparison between four text classification algorithms - Naïve Bayes, Support Vector Machine, Decision Tree and Random Forest, using different feature extraction techniques, such as ...
Our experiments revealed that Support Vector Machine achieves the best results and is very suitable for classification of the sentiment on product reviews. ...
(Bansal, 2018) applied deep learning methods such as, CBOW and skip-gram, with different machine learning algorithms: SVM, Naïve Bayes, Logistic Regression and Random Forest. ...
doaj:0182bdc144724c71abdaf29f7c56f655
fatcat:qj73wydaavfgdike4v34ejsooi
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