Accesso libero

A Topic Detection Method Based on Word-attention Networks

   | 18 ago 2021
INFORMAZIONI SU QUESTO ARTICOLO

Cita

Agrawal, R., & Srikant, R. (1994, September). Fast algorithms for mining association rules. In Proceedings of the 20th International Conference of Very Large Data Bases. 1215, 487–499. AgrawalR. SrikantR. 1994 September Fast algorithms for mining association rules In Proceedings of the 20th International Conference of Very Large Data Bases 1215 487 499 Search in Google Scholar

Ahn, Y.Y., Bagrow, J.P., & Lehmann, S. (2010). Link communities reveal multiscale complexity in networks. nature, 466(7307), 761–764. AhnY.Y. BagrowJ.P. LehmannS. 2010 Link communities reveal multiscale complexity in networks Nature 466 7307 761 764 10.1038/nature0918220562860 Search in Google Scholar

Asuncion, A., Welling, M., Smyth, P., & Teh, Y.W. (2012). On smoothing and inference for topic models. UAI Press. arXiv:1205.2662. AsuncionA. WellingM. SmythP. TehY.W. 2012 On smoothing and inference for topic models UAI Press arXiv:1205.2662. Search in Google Scholar

Blei, D.M., Ng, A.Y., & Jordan, M.I. (2003). Latent dirichlet allocation. the Journal of machine Learning research, 3, 993–1022. BleiD.M. NgA.Y. JordanM.I. 2003 Latent dirichlet allocation the Journal of machine Learning research 3 993 1022 Search in Google Scholar

Blondel, V.D., Guillaume, J.L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and experiment, 2008(10), P10008. BlondelV.D. GuillaumeJ.L. LambiotteR. LefebvreE. 2008 Fast unfolding of communities in large networks Journal of Statistical Mechanics: Theory and experiment 2008 10 P10008 10.1088/1742-5468/2008/10/P10008 Search in Google Scholar

Boyack, K.W., Newman, D., Duhon, R.J., Klavans, R., Patek, M., Biberstine, J.R., ... & Börner, K. (2011). Clustering more than two million biomedical publications: Comparing the accuracies of nine text-based similarity approaches. PloS one, 6(3), e18029. BoyackK.W. NewmanD. DuhonR.J. KlavansR. PatekM. BiberstineJ.R. BörnerK. 2011 Clustering more than two million biomedical publications: Comparing the accuracies of nine text-based similarity approaches PloS one 6 3 e18029 10.1371/journal.pone.0018029306009721437291 Search in Google Scholar

Cheng, J.P., Dong, L., & Lapata, M. (2016). Long short-term memory-networks for machine reading. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 551–561. ChengJ.P. DongL. LapataM. 2016 Long short-term memory-networks for machine reading Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing 551 561 10.18653/v1/D16-1053 Search in Google Scholar

Doucet, A., & Ahonen-Myka, H. (2010). An efficient any language approach for the integration of phrases in document retrieval. Language resources and evaluation, 44(1), 159–180. DoucetA. Ahonen-MykaH. 2010 An efficient any language approach for the integration of phrases in document retrieval Language resources and evaluation 44 1 159 180 10.1007/s10579-009-9102-3 Search in Google Scholar

Gehring, J., Auli, M., Grangier, D., Yarats, D., & Dauphin, Y.N. (2017, July). Convolutional sequence to sequence learning. In International Conference on Machine Learning. 1243–1252. GehringJ. AuliM. GrangierD. YaratsD. DauphinY.N. 2017 July Convolutional sequence to sequence learning In International Conference on Machine Learning 1243 1252 Search in Google Scholar

Gildea, D., & Jurafsky, D. (2002). Automatic labeling of semantic roles. Computational Linguistics, 28(3), 245–288. GildeaD. JurafskyD. 2002 Automatic labeling of semantic roles Computational Linguistics 28 3 245 288 10.3115/1075218.1075283 Search in Google Scholar

Girvan, M., & Newman, M.E. (2002). Community structure in social and biological networks. Proceedings of the National Academy of Sciences, 99(12), 7821–7826. GirvanM. NewmanM.E. 2002 Community structure in social and biological networks Proceedings of the National Academy of Sciences 99 12 7821 7826 10.1073/pnas.12265379912297712060727 Search in Google Scholar

Griffiths, T.L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences, 101(suppl 1), 5228–5235. GriffithsT.L. SteyversM. 2004 Finding scientific topics Proceedings of the National Academy of Sciences 101 suppl 1 5228 5235 10.1073/pnas.030775210138730014872004 Search in Google Scholar

Hochreiter, S., & Schmidhuber, J. (1997). Long short-term memory. Neural Computation, 9(8), 1735–1780. HochreiterS. SchmidhuberJ. 1997 Long short-term memory Neural Computation 9 8 1735 1780 10.1162/neco.1997.9.8.17359377276 Search in Google Scholar

Kalchbrenner, N., et al. Espeholt, L., Simonyan, K., Oord, A.V.D., Graves, A., & Kavukcuoglu, K. (2016). Neural machine translation in linear time. arXiv preprint arXiv:1610.10099. KalchbrennerN. EspeholtL. SimonyanK. OordA.V.D. GravesA. KavukcuogluK. 2016 Neural machine translation in linear time arXiv preprint arXiv:1610.10099. Search in Google Scholar

Kim, Y., Denton, C., Hoang, L., & Rush, A.M. (2017). Structured attention networks. In International Conference on Learning Representations. arXiv:1702.00887 KimY. DentonC. HoangL. RushA.M. 2017 Structured attention networks In International Conference on Learning Representations arXiv:1702.00887 Search in Google Scholar

Kingsbury, P., & Palmer, M. (2002). From treebank to propbank. Language Resources & Evaluation. Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02). KingsburyP. PalmerM. 2002 From treebank to propbank. Language Resources & Evaluation Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02) Search in Google Scholar

Leicht, E.A., & Newman, M.E. (2008). Community structure in directed networks. Physical Review Letters, 100(11), 118703. LeichtE.A. NewmanM.E. 2008 Community structure in directed networks Physical Review Letters 100 11 118703 10.1103/PhysRevLett.100.11870318517839 Search in Google Scholar

Li, P.J., Lam, W., Bing, L., & Wang, Z. (2017). Deep Recurrent Generative Decoder for Abstractive Text Summarization. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2081–2090. LiP.J. LamW. BingL. WangZ. 2017 Deep Recurrent Generative Decoder for Abstractive Text Summarization Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing 2081 2090 10.18653/v1/D17-1221 Search in Google Scholar

McDonald, R., Pereira, F., Kulick, S., Winters, S., Jin, Y., & White, P. (2005, June). Simple algorithms for complex relation extraction with applications to biomedical IE. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL05). 491–498. McDonaldR. PereiraF. KulickS. WintersS. JinY. WhiteP. 2005 June Simple algorithms for complex relation extraction with applications to biomedical IE In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL05) 491 498 10.3115/1219840.1219901 Search in Google Scholar

Mintz, M., Bills, S., Snow, R., & Jurafsky, D. (2009, August). Distant supervision for relation extraction without labeled data. In Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP. 1003–1011. MintzM. BillsS. SnowR. JurafskyD. 2009 August Distant supervision for relation extraction without labeled data In Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP 1003 1011 10.3115/1690219.1690287 Search in Google Scholar

Pons, P., & Latapy, M. (2005, October). Computing communities in large networks using random walks. International symposium on computer and information sciences. ISCIS 2005: Computer and Information Sciences - ISCIS 2005, 284–293. PonsP. LatapyM. 2005 October Computing communities in large networks using random walks International symposium on computer and information sciences. ISCIS 2005: Computer and Information Sciences - ISCIS 2005 284 293 10.1007/11569596_31 Search in Google Scholar

Ramage, D., Manning, C.D., & Dumais, S. (2011, August). Partially labeled topic models for interpretable text mining. In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 457–465. 457–465. RamageD. ManningC.D. DumaisS. 2011 August Partially labeled topic models for interpretable text mining In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 457 465 457–465. 10.1145/2020408.2020481 Search in Google Scholar

Schmidhuber, J. (2001). Gradient Flow in Recurrent Nets: The Difficulty of Learning Long-Term Dependencies. Wiley-IEEE Press. SchmidhuberJ. 2001 Gradient Flow in Recurrent Nets: The Difficulty of Learning Long-Term Dependencies Wiley-IEEE Press Search in Google Scholar

Sethy, A., & Ramabhadran, B. (2008). Bag-of-word normalized n-gram models. In Ninth Annual Conference of the International Speech Communication Association. 1594–1597. SethyA. RamabhadranB. 2008 Bag-of-word normalized n-gram models In Ninth Annual Conference of the International Speech Communication Association 1594 1597 10.21437/Interspeech.2008-265 Search in Google Scholar

Shannon, C.E. (1948). A mathematical theory of communication. The Bell System Technical Journal, 27(3), 379–423. ShannonC.E. 1948 A mathematical theory of communication The Bell System Technical Journal 27 3 379 423 10.1002/j.1538-7305.1948.tb01338.x Search in Google Scholar

Small, H., Boyack, K.W., & Klavans, R. (2014). Identifying emerging topics in science and technology. Research policy, 43(8), 1450–1467. SmallH. BoyackK.W. KlavansR. 2014 Identifying emerging topics in science and technology Research policy 43 8 1450 1467 10.1016/j.respol.2014.02.005 Search in Google Scholar

Swampillai, K., & Stevenson, M. (2011, September). Extracting relations within and across sentences. In Proceedings of the International Conference Recent Advances in Natural Language Processing 2011. 25–32. SwampillaiK. StevensonM. 2011 September Extracting relations within and across sentences In Proceedings of the International Conference Recent Advances in Natural Language Processing 2011 25 32 Search in Google Scholar

Talley, E.M., Newman, D., Mimno, D., Herr, B.W., Wallach, H.M., Burns, G.A., ... & McCallum, A. (2011). Database of NIH grants using machine-learned categories and graphical clustering. Nature Methods, 8(6), 443–444. TalleyE.M. NewmanD. MimnoD. HerrB.W. WallachH.M. BurnsG.A. McCallumA. 2011 Database of NIH grants using machine-learned categories and graphical clustering Nature Methods 8 6 443 444 10.1038/nmeth.1619536121621623347 Search in Google Scholar

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., & Polosukhin, I. (2017). Attention is all you need. In Advances in neural information processing systems. 5998–6008. VaswaniA. ShazeerN. ParmarN. UszkoreitJ. JonesL. GomezA.N. KaiserL. PolosukhinI. 2017 Attention is all you need In Advances in neural information processing systems 5998 6008 Search in Google Scholar

Velden, T., Boyack, K.W., Gläser, J., Koopman, R., Scharnhorst, A., & Wang, S. (2017). Comparison of topic extraction approaches and their results. Scientometrics, 111(2), 1169–1221. VeldenT. BoyackK.W. GläserJ. KoopmanR. ScharnhorstA. WangS. 2017 Comparison of topic extraction approaches and their results Scientometrics 111 2 1169 1221 10.1007/s11192-017-2306-1 Search in Google Scholar

Wallach, H.M. (2006, June). Topic modeling: Beyond bag-of-words. In Proceedings of the 23rd international conference on Machine learning, 977–984. WallachH.M. 2006 June Topic modeling: Beyond bag-of-words In Proceedings of the 23rd international conference on Machine learning 977 984 10.1145/1143844.1143967 Search in Google Scholar

Yin, W., Schütze, H., Xiang, B., & Zhou, B. (2016). Abcnn: Attention-based convolutional neural network for modeling sentence pairs. Transactions of the Association for Computational Linguistics, 4, 259–272. YinW. SchützeH. XiangB. ZhouB. 2016 Abcnn: Attention-based convolutional neural network for modeling sentence pairs Transactions of the Association for Computational Linguistics 4 259 272 10.1162/tacl_a_00097 Search in Google Scholar

Zeng, D.J., Liu, K., Lai, S., Zhou, G., & Zhao, J. (2014, August). Relation classification via convolutional deep neural network. In Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers. 2335–2344. ZengD.J. LiuK. LaiS. ZhouG. ZhaoJ. 2014 August Relation classification via convolutional deep neural network In Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers 2335 2344 Search in Google Scholar

Zhang, Y., Lu, J., Liu, F., Liu, Q., Porter, A., Chen, H., & Zhang, G. (2018). Does deep learning help topic extraction? A kernel k-means clustering method with word embedding. Journal of Informetrics, 12(4), 1099–1117. ZhangY. LuJ. LiuF. LiuQ. PorterA. ChenH. ZhangG. 2018 Does deep learning help topic extraction? A kernel k-means clustering method with word embedding Journal of Informetrics 12 4 1099 1117 10.1016/j.joi.2018.09.004 Search in Google Scholar

eISSN:
2543-683X
Lingua:
Inglese
Frequenza di pubblicazione:
4 volte all'anno
Argomenti della rivista:
Computer Sciences, Information Technology, Project Management, Databases and Data Mining