%0 Conference Paper %1 shi2019recommendation %A Shi, Xuewen %A Huang, Heyan %A Zhao, Shuyang %A Jian, Ping %A Tang, Yi-Kun %B Database Systems for Advanced Applications %C Cham %D 2019 %E Li, Guoliang %E Yang, Jun %E Gama, Joao %E Natwichai, Juggapong %E Tong, Yongxin %I Springer International Publishing %K paper:neural_tag recommendation seq2seq tag %P 420--424 %T Tag Recommendation by Word-Level Tag Sequence Modeling %X In this paper, we transform tag recommendation into a word-based text generation problem and introduce a sequence-to-sequence model. The model inherits the advantages of LSTM-based encoder for sequential modeling and attention-based decoder with local positional encodings for learning relations globally. Experimental results on Zhihu datasets illustrate the proposed model outperforms other state-of-the-art text classification based methods. %@ 978-3-030-18590-9

@inproceedings{shi2019recommendation, abstract = {In this paper, we transform tag recommendation into a word-based text generation problem and introduce a sequence-to-sequence model. The model inherits the advantages of LSTM-based encoder for sequential modeling and attention-based decoder with local positional encodings for learning relations globally. Experimental results on Zhihu datasets illustrate the proposed model outperforms other state-of-the-art text classification based methods.}, added-at = {2019-07-01T22:53:18.000+0200}, address = {Cham}, author = {Shi, Xuewen and Huang, Heyan and Zhao, Shuyang and Jian, Ping and Tang, Yi-Kun}, biburl = {https://www.bibsonomy.org/bibtex/2e812f675b8cb81623b3a483c3111cf6d/nosebrain}, booktitle = {Database Systems for Advanced Applications}, description = {Tag Recommendation by Word-Level Tag Sequence Modeling | SpringerLink}, editor = {Li, Guoliang and Yang, Jun and Gama, Joao and Natwichai, Juggapong and Tong, Yongxin}, interhash = {02e437b6b540f944c96d48c2fcb6af29}, intrahash = {e812f675b8cb81623b3a483c3111cf6d}, isbn = {978-3-030-18590-9}, keywords = {paper:neural_tag recommendation seq2seq tag}, pages = {420--424}, publisher = {Springer International Publishing}, timestamp = {2019-07-01T22:53:18.000+0200}, title = {Tag Recommendation by Word-Level Tag Sequence Modeling}, year = 2019 }