,
,
,
, , pp.97-141
,
,
,
, References
Modern Information Retrieval, 1999. ,
Neural Probabilistic Language Models, J. Mach. Learn. Res, vol.3, pp.1137-1155, 2003. ,
DOI : 10.1007/3-540-33486-6_6
URL : https://hal.archives-ouvertes.fr/hal-01434258
Graph-based term weighting for information retrieval, Information Retrieval, vol.393, issue.3, pp.54-92, 2012. ,
DOI : 10.1038/30918
Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification, Association for Computational Linguistics, 2007. ,
A convolutional neural network for modelling sentences, Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics. Proceedings of the 52nd Annual Meeting of the Association for Computational Lin- guistics, 2014. ,
A comparison of centrality measures for graph-based keyphrase extraction, IJC- NLP, pp.834-838, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-00850187
Supervised term weighting for automated text categorization, Text mining and its applications, pp.81-97, 2004. ,
DOI : 10.1145/952686.952688
URL : http://faure.iei.pi.cnr.it/~fabrizio/Publications/SAC03b.pdf
Frequent substructure-based approaches for classifying chemical compounds, IEEE Transactions on Knowledge and Data Engineering, vol.17, issue.8, pp.1036-1050, 2005. ,
DOI : 10.1109/TKDE.2005.127
URL : http://www-users.cs.umn.edu/~karypis/publications/Papers/PDF/chemclassify.pdf
LexRank: Graph-based Lexical Centrality as Salience in Text Summarization, Journal of Artificial Intelligence Research, vol.22, issue.1, pp.457-479, 2004. ,
DOI : 10.1613/jair.1523
URL : https://jair.org/index.php/jair/article/download/10396/24901
Random-walk term weighting for improved text classification, ICSC, pp.242-249, 2007. ,
DOI : 10.1109/icosc.2007.4338355
URL : https://digital.library.unt.edu/ark:/67531/metadc30994/m2/1/high_res_d/Mihalcea-2007-Random-Walk_Term_Weighting_for_Improved.pdf
A new term ranking method based on relation extraction and graph model for text classification, Proceedings of the Thirty-Fourth Australasian Computer Science Conference, pp.145-152, 2011. ,
Text classification using graph mining-based feature extraction. Knowl.-Based Syst, pp.302-308, 2010. ,
DOI : 10.1016/j.knosys.2009.11.010
URL : http://www.csc.liv.ac.uk/~frans/PostScriptFiles/ai09jiang.pdf
Text categorization with suport vector machines: Learning with many relevant features, ECML, pp.137-142, 1998. ,
DOI : 10.1007/bfb0026683
URL : https://link.springer.com/content/pdf/10.1007%2FBFb0026683.pdf
Effective Use of Word Order for Text Categorization with Convolutional Neural Networks, Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp.103-112, 2015. ,
DOI : 10.3115/v1/N15-1011
URL : https://doi.org/10.3115/v1/n15-1011
Bag of Tricks for Efficient Text Classification, Proceedings of the 15th Conference of the European Chapter of the
Association for Computational Linguistics: Volume 2, Short Papers, pp.427-431, 2017. ,
DOI : 10.18653/v1/E17-2068
URL : https://doi.org/10.18653/v1/e17-2068
Some effective techniques for naive bayes text classification, IEEE Trans. Knowl. Data Eng, vol.18, issue.11, pp.1457-1466, 2006. ,
Convolutional Neural Networks for Sentence Classification, Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2014. ,
DOI : 10.3115/v1/D14-1181
URL : https://doi.org/10.3115/v1/d14-1181
From word embeddings to document distances, International Conference on Machine Learning, pp.957-966, 2015. ,
Keyword and keyphrase extraction using centrality measures on collocation networks, 2014. ,
A comprehensive comparative study on term weighting schemes for text categorization with support vector machines, Special interest tracks and posters of the 14th international conference on World Wide Web , WWW '05, pp.1032-1033, 2005. ,
DOI : 10.1145/1062745.1062854
URL : http://www.comp.nus.edu.sg/~tancl/Papers/WWW05/POS806-Lan.pdf
Convolutional networks for images, speech, and time series. The handbook of brain theory and neural networks, p.3361, 1995. ,
Molding CNNs for text: non-linear, non-consecutive convolutions, Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015. ,
DOI : 10.18653/v1/D15-1180
URL : https://doi.org/10.18653/v1/d15-1180
Text categorization with support vector machines. How to represent texts in input space?, Mach. Learn, vol.46, pp.1-3, 2002. ,
Graph-based keyword extraction for single-document summarization, Proceedings of the Workshop on Multi-source Multilingual Information Extraction and Summarization, MMIES '08, pp.17-24, 2008. ,
DOI : 10.3115/1613172.1613178
URL : http://dl.acm.org/ft_gateway.cfm?id=1613178&type=pdf
Graph-based term weighting for text categorization, Proceedings of ASONAM, pp.1473-1479, 2015. ,
Delta tfidf: An improved feature space for sentiment analysis, ICWSM, 2009. ,
A comparison of event models for naive bayes text classification, AAAI: Proceedings of the Workshop on Learning for Text Categorization, pp.41-48, 1998. ,
Textrank: Bringing order into text, EMNLP, pp.404-411, 2004. ,
Distributed representations of words and phrases and their compositionality, Advances in neural information processing systems, pp.3111-3119, 2013. ,
Networks: An Introduction, 2010. ,
DOI : 10.1093/acprof:oso/9780199206650.001.0001
Text classification from labeled and unlabeled documents using EM, Machine Learning, vol.39, issue.2/3, pp.103-134, 2000. ,
DOI : 10.1023/A:1007692713085
Yannis Stavrakas, and Michalis Vazirgiannis . 2017. Shortest-path graph kernels for document similarity, Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp.1890-1900 ,
A study of information retrieval weighting schemes for sentiment analysis, ACL, pp.1386-1395, 2010. ,
A sentimental education, Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics , ACL '04, 2004. ,
DOI : 10.3115/1218955.1218990
Understanding inverse document frequency: on theoretical arguments for IDF, Journal of Documentation, vol.60, issue.5, 2004. ,
DOI : 10.1016/S0306-4573(00)00015-7
Okapi at trec-3, Nist Special Publication Sp, vol.109, p.109, 1995. ,
Graph-of-word and TW-IDF, Proceedings of the 22nd ACM international conference on Conference on information & knowledge management, CIKM '13, pp.59-68, 2013. ,
DOI : 10.1145/2505515.2505671
Main core retention on graph-of-words for singledocument keyword extraction, ECIR, pp.382-393, 2015. ,
DOI : 10.1007/978-3-319-16354-3_42
Text Categorization as a Graph Classification Problem, Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), 2015. ,
DOI : 10.3115/v1/P15-1164
URL : https://doi.org/10.3115/v1/p15-1164
Term-weighting approaches in automatic text retrieval, Information Processing & Management, vol.24, issue.5, pp.513-523, 1988. ,
DOI : 10.1016/0306-4573(88)90021-0
URL : http://ecommons.cornell.edu/bitstream/1813/6721/1/87-881.pdf
Machine learning in automated text categorization, ACM Computing Surveys, vol.34, issue.1, pp.1-47, 2002. ,
DOI : 10.1145/505282.505283
URL : http://arxiv.org/pdf/cs/0110053
Centrality-Based Approach for Supervised Term Weighting, 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW), pp.1261-1268, 2016. ,
DOI : 10.1109/ICDMW.2016.0181
N-gram IDF, Proceedings of the 24th International Conference on World Wide Web, WWW '15, 2015. ,
DOI : 10.1016/j.eswa.2009.02.026
Pivoted document length normalization, SIGIR, pp.21-29, 1996. ,
Corpus-independent generic keyphrase extraction using word embedding vectors, 2015. ,
Character-level convolutional networks for text classification, Advances in Neural Information Processing Systems, pp.649-657, 2015. ,