AUTOMATSKI GENERISANJE KULINARSKIH RECEPATA OD DATIH SASTOJAKA
Ključne reči:
generisanje recepata, generisanje prirod¬nog jezika, sequence to sequence modeli
Apstrakt
Sa porastom popularnosti online stranica za deljenje recepata, količina raspoloživih podataka iz oblasti kulinarstva je veća nego ikad. Ljudi su u konstantnoj potrazi za načinom da brzo pronađu i spreme obrok. U ovom radu predložen je sistem za automatsko generisanje recepata za sastojke koje korisnik ima na raspolaganju, upotrebom sequence to sequence modela, kao i odabir podskupa sastojaka koji najbolje idu jedni uz druge. Pokazano je da je moguće generisati smislene tekstove recepata iz bilo kojeg unetog skupa sastojaka, ali se dovodi u pitanje njihova upotrebljivost u praksi. Uvođenjem novih ideja obrade sastojaka, ovaj rad donosi dobru osnovu za dalja istraživanja i unapređenja u ovom polju.
Reference
[1] Sutskever, Ilya, Oriol Vinyals, and Quoc V. Le. "Sequence to sequence learning with neural networks."
[2] Ramachandran, Prajit, et al. "Stand-alone self-attention in vision models." arXiv preprint arXiv:1906.05909 (2019).
[3] Vaswani, Ashish, et al. "Attention is all you need." Advances in neural information processing systems. 2017.
[4] Marin, Javier, et al. "Recipe1m+: A dataset for learning cross-modal embeddings for cooking recipes and food images." IEEE transactions on pattern analysis and machine intelligence 43.1 (2019): 187-203.
[5] Goldberg, Yoav, and Omer Levy. "word2vec Explained: deriving Mikolov et al.'s negative-sampling word-embedding method." arXiv preprint arXiv:1402.3722 (2014).
[6] H. Lee, Helena, et al. "RecipeGPT: Generative pre-training based cooking recipe generation and evaluation system." Companion Proceedings of the Web Conference 2020. 2020.
[7] Radford, Alec, et al. "Language models are unsupervised multitask learners." OpenAI blog 1.8 (2019): 9.
[8] Papineni, Kishore, et al. "Bleu: a method for automatic evaluation of machine translation." Proceedings of the 40th annual meeting of the Association for Computational Linguistics. 2002.
[9] Lin, Chin-Yew. "Rouge: A package for automatic evaluation of summaries." Text summarization branches out. 2004.
[10] Teisberg, Dev Bhargava Thomas. "Recipe for Disaster: A Seq2Seq Model for Recipe."
[11] Luong, Minh-Thang, Hieu Pham, and Christopher D. Manning. "Effective approaches to attention-based neural machine translation." arXiv preprint arXiv:1508.04025 (2015).
[12] Chorowski, Jan, et al. "Attention-based models for speech recognition." arXiv preprint arXiv:1506.07503 (2015).
[13] Cho, Kyunghyun, et al. "Learning phrase representations using RNN encoder-decoder for statistical machine translation." arXiv preprint arXiv:1406.1078 (2014).
[14] Devlin, Jacob, et al. "Bert: Pre-training of deep bidirectional transformers for language understanding." arXiv preprint arXiv:1810.04805 (2018).
[2] Ramachandran, Prajit, et al. "Stand-alone self-attention in vision models." arXiv preprint arXiv:1906.05909 (2019).
[3] Vaswani, Ashish, et al. "Attention is all you need." Advances in neural information processing systems. 2017.
[4] Marin, Javier, et al. "Recipe1m+: A dataset for learning cross-modal embeddings for cooking recipes and food images." IEEE transactions on pattern analysis and machine intelligence 43.1 (2019): 187-203.
[5] Goldberg, Yoav, and Omer Levy. "word2vec Explained: deriving Mikolov et al.'s negative-sampling word-embedding method." arXiv preprint arXiv:1402.3722 (2014).
[6] H. Lee, Helena, et al. "RecipeGPT: Generative pre-training based cooking recipe generation and evaluation system." Companion Proceedings of the Web Conference 2020. 2020.
[7] Radford, Alec, et al. "Language models are unsupervised multitask learners." OpenAI blog 1.8 (2019): 9.
[8] Papineni, Kishore, et al. "Bleu: a method for automatic evaluation of machine translation." Proceedings of the 40th annual meeting of the Association for Computational Linguistics. 2002.
[9] Lin, Chin-Yew. "Rouge: A package for automatic evaluation of summaries." Text summarization branches out. 2004.
[10] Teisberg, Dev Bhargava Thomas. "Recipe for Disaster: A Seq2Seq Model for Recipe."
[11] Luong, Minh-Thang, Hieu Pham, and Christopher D. Manning. "Effective approaches to attention-based neural machine translation." arXiv preprint arXiv:1508.04025 (2015).
[12] Chorowski, Jan, et al. "Attention-based models for speech recognition." arXiv preprint arXiv:1506.07503 (2015).
[13] Cho, Kyunghyun, et al. "Learning phrase representations using RNN encoder-decoder for statistical machine translation." arXiv preprint arXiv:1406.1078 (2014).
[14] Devlin, Jacob, et al. "Bert: Pre-training of deep bidirectional transformers for language understanding." arXiv preprint arXiv:1810.04805 (2018).
Objavljeno
2022-07-04
Sekcija
Elektrotehničko i računarsko inženjerstvo
