{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T19:10:50Z","timestamp":1754161850814,"version":"3.41.2"},"reference-count":41,"publisher":"Association for Computing Machinery (ACM)","issue":"1","funder":[{"DOI":"10.13039\/501100001659","name":"German Research Foundation","doi-asserted-by":"crossref","award":["438232455 (HydrAS)"],"award-info":[{"award-number":["438232455 (HydrAS)"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"crossref"}]},{"name":"German Federal Ministry of Education and Research","award":["01IS22051B (KILiMod)"],"award-info":[{"award-number":["01IS22051B (KILiMod)"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Recomm. Syst."],"published-print":{"date-parts":[[2026,3,31]]},"abstract":"<jats:p>Analyzing sequences of interactions between users and items, sequential recommendation models can learn user intent and make predictions about the next item. Next to item interactions, most systems also have interactions with what we call non-item pages: these pages are not related to specific items but still can provide insights into the user\u2019s interests, as, for example, navigation pages. We therefore propose a general way to include these non-item pages in sequential recommendation models to enhance next-item prediction.<\/jats:p>\n          <jats:p>First, we demonstrate the influence of non-item pages on following interactions using the hypotheses testing framework HypTrails and propose methods for representing non-item pages in sequential recommendation models. Subsequently, we adapt popular sequential recommender models to integrate non-item pages and investigate their performance with different item representation strategies as well as their ability to handle noisy data. To show the general capabilities of the models to integrate non-item pages, we create a synthetic dataset for a controlled setting and then evaluate the improvements from including non-item pages on two real-world datasets.<\/jats:p>\n          <jats:p>Our results show that non-item pages are a valuable source of information, and incorporating them in sequential recommendation models increases the performance of next-item prediction across all analyzed model architectures.<\/jats:p>","DOI":"10.1145\/3721298","type":"journal-article","created":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T06:33:33Z","timestamp":1741242813000},"page":"1-39","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Modeling and Analyzing the Influence of Non-Item Pages on Sequential Next-Item Prediction"],"prefix":"10.1145","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-7371-052X","authenticated-orcid":false,"given":"Elisabeth","family":"Fischer","sequence":"first","affiliation":[{"name":"CAIDAS - Data Science Chair, University of W\u00fcrzburg","place":["W\u00fcrzburg, Germany"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9472-0783","authenticated-orcid":false,"given":"Albin","family":"Zehe","sequence":"additional","affiliation":[{"name":"CAIDAS - Data Science Chair, University of W\u00fcrzburg","place":["W\u00fcrzburg, Germany"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0483-5772","authenticated-orcid":false,"given":"Andreas","family":"Hotho","sequence":"additional","affiliation":[{"name":"CAIDAS - Data Science Chair, University of W\u00fcrzburg","place":["W\u00fcrzburg, Germany"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-6983-3719","authenticated-orcid":false,"given":"Daniel","family":"Schl\u00f6r","sequence":"additional","affiliation":[{"name":"CAIDAS - Data Science Chair, University of W\u00fcrzburg","place":["W\u00fcrzburg, Germany"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,7,29]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/3326937.3341261"},{"key":"e_1_3_3_3_2","unstructured":"Kevin Clark Minh-Thang Luong Quoc V. Le and Christopher D. Manning. 2020. ELECTRA: Pre-training text encoders as discriminators rather than generators. In CoRR. Retrieved from https:\/\/arxiv.org\/abs\/2003.10555"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/3460231.3475943"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/3460231.3474255"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N19-1423"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","unstructured":"Xinyan Fan Zheng Liu Jianxun Lian Wayne Zhao Xing Xie and Ji-Rong Wen. 2021. Lighter and better: Low-rank decomposed self-attention networks for next-item recommendation. 1733\u20131737. DOI:10.1145\/3404835.3462978","DOI":"10.1145\/3404835.3462978"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW60847.2023.00024"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58285-2_23"},{"key":"e_1_3_3_10_2","unstructured":"Elisabeth Fischer Daniel Zoller and Andreas Hotho. 2021. Comparison of transformer-based sequential product recommendation models for the coveo data challenge. In SIGIR 2021 Workshop on eCommerce."},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271761"},{"key":"e_1_3_3_12_2","volume-title":"Proceedings of the ICLR (Poster)","author":"Hidasi Bal\u00e1zs","year":"2016","unstructured":"Bal\u00e1zs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, and Domonkos Tikk. 2016. Session-based recommendations with recurrent neural networks. In Proceedings of the ICLR (Poster). Yoshua Bengio and Yann LeCun (Eds.)."},{"key":"e_1_3_3_13_2","doi-asserted-by":"publisher","DOI":"10.1145\/2959100.2959167"},{"key":"e_1_3_3_14_2","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531955"},{"key":"e_1_3_3_15_2","unstructured":"Shotaro Ishihara Shuhei Goda and Hidehisa Arai. 2021. Adversarial validation to select validation data for evaluating performance in e-commerce purchase intent prediction. In SIGIR 2021 Workshop on eCommerce."},{"key":"e_1_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3594714"},{"key":"e_1_3_3_17_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2018.00035"},{"key":"e_1_3_3_18_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-023-00996-8"},{"key":"e_1_3_3_19_2","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132926"},{"key":"e_1_3_3_20_2","doi-asserted-by":"publisher","unstructured":"Chang Liu Xiaoguang Li Guohao Cai Zhenhua Dong Hong Zhu and Lifeng Shang. 2021. Noninvasive self-attention for side information fusion in sequential recommendation. Proceedings of the AAAI Conference on Artificial Intelligence 35 5 (May 2021) 4249\u20134256. DOI:10.1609\/aaai.v35i5.16549","DOI":"10.1609\/aaai.v35i5.16549"},{"key":"e_1_3_3_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2016.0135"},{"key":"e_1_3_3_22_2","article-title":"Visualizing data using t-SNE","author":"Maaten L.","year":"2008","unstructured":"L. Maaten and Geoffrey E. Hinton. 2008. Visualizing data using t-SNE. Journal of Machine Learning Research (2008). Retrieved from https:\/\/www.semanticscholar.org\/paper\/Visualizing-Data-using-t-SNE-Maaten-Hinton\/1c46943103bd7b7a2c7be86859995a4144d1938b","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_3_23_2","unstructured":"Gabriel de Souza P. Moreira Sara Rabhi Ronay Ak Md Yasin Kabir and Even Oldridge. 2021. Transformers with multi-modal features and post-fusion context for e-commerce session-based recommendation. In SIGIR 2021 Workshop on eCommerce."},{"key":"e_1_3_3_24_2","doi-asserted-by":"publisher","DOI":"10.1145\/3523227.3548487"},{"key":"e_1_3_3_25_2","unstructured":"Yoshihiro Sakatani. 2021. Session-based recommendation using an ensemble of LSTM-and matrix factorization-based models. In SIGIR 2021 Workshop on eCommerce."},{"key":"e_1_3_3_26_2","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741080"},{"key":"e_1_3_3_27_2","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357895"},{"key":"e_1_3_3_28_2","unstructured":"Jacopo Tagliabue Ciro Greco Jean-Francis Roy Bingqing Yu Patrick John Chia Federico Bianchi and Giovanni Cassani. 2021. SIGIR 2021 E-Commerce workshop data challenge. In SIGIR 2021 Workshop on eCommerce."},{"key":"e_1_3_3_29_2","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988452"},{"key":"e_1_3_3_30_2","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159656"},{"key":"e_1_3_3_31_2","doi-asserted-by":"publisher","unstructured":"Wilson L. Taylor. 1953. \u201cCloze Procedure\u201d: A new tool for measuring readability. Journalism & Mass Communication Quarterly 30 4 (September 1953) 415\u2013433. DOI:10.1177\/107769905303000401","DOI":"10.1177\/107769905303000401"},{"key":"e_1_3_3_32_2","doi-asserted-by":"publisher","DOI":"10.1145\/3109859.3109900"},{"key":"e_1_3_3_33_2","first-page":"5998","volume-title":"Proceedings of the Advances in Neural Information Processing Systems","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. In Proceedings of the Advances in Neural Information Processing Systems. 5998\u20136008."},{"key":"e_1_3_3_34_2","doi-asserted-by":"publisher","DOI":"10.23915\/distill.00002"},{"key":"e_1_3_3_35_2","doi-asserted-by":"publisher","DOI":"10.1145\/3383313.3412258"},{"key":"e_1_3_3_36_2","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531963"},{"key":"e_1_3_3_37_2","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313408"},{"key":"e_1_3_3_38_2","volume-title":"Proceedings of the 33rd International Conference on Neural Information Processing Systems","author":"Yang Zhilin","year":"2019","unstructured":"Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, and Quoc V. Le. 2019. XLNet: Generalized autoregressive pretraining for language understanding. In Proceedings of the 33rd International Conference on Neural Information Processing Systems. Curran Associates Inc., Red Hook, NY, USA."},{"key":"e_1_3_3_39_2","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3290975"},{"key":"e_1_3_3_40_2","unstructured":"Albin Zehe Elisabeth Fischer Jonas Kaiser Toni Wagner and Andreas Hotho. 2024. Adapting sequential recommender models to content recommendation in chat data using non-item page-models. In Proceedings of the Sixth Knowledge-aware and Conversational Recommender Systems Workshop. CEUR-WS.org Bari 66\u201384. https:\/\/ceur-ws.org\/Vol-3817\/"},{"key":"e_1_3_3_41_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3069058"},{"key":"e_1_3_3_42_2","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482016"}],"container-title":["ACM Transactions on Recommender Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3721298","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,29]],"date-time":"2025-07-29T12:47:32Z","timestamp":1753793252000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3721298"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,29]]},"references-count":41,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,3,31]]}},"alternative-id":["10.1145\/3721298"],"URL":"https:\/\/doi.org\/10.1145\/3721298","relation":{},"ISSN":["2770-6699"],"issn-type":[{"type":"electronic","value":"2770-6699"}],"subject":[],"published":{"date-parts":[[2025,7,29]]},"assertion":[{"value":"2024-09-25","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-02-15","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-29","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}