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- research-articleAugust 2023
S2phere: Semi-Supervised Pre-training for Web Search over Heterogeneous Learning to Rank Data
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 4437–4448https://doi.org/10.1145/3580305.3599935While Learning to Rank (LTR) models on top of transformers have been widely adopted to achieve decent performance, it is still challenging to train the model with sufficient data as only an extremely small number of query-webpage pairs could be annotated ...
- research-articleAugust 2023
Workplace Recommendation with Temporal Network Objectives
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 4958–4969https://doi.org/10.1145/3580305.3599932Workplace communication software such as Microsoft Teams, Slack, and Google Workspace have become integral to workplace collaboration, especially due to the rise of remote work. By making it easier to access relevant or useful information, recommender ...
- research-articleAugust 2023
TwHIN-BERT: A Socially-Enriched Pre-trained Language Model for Multilingual Tweet Representations at Twitter
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 5597–5607https://doi.org/10.1145/3580305.3599921Pre-trained language models (PLMs) are fundamental for natural language processing applications. Most existing PLMs are not tailored to the noisy user-generated text on social media, and the pre-training does not factor in the valuable social engagement ...
- research-articleAugust 2023
TransAct: Transformer-based Realtime User Action Model for Recommendation at Pinterest
- Xue Xia,
- Pong Eksombatchai,
- Nikil Pancha,
- Dhruvil Deven Badani,
- Po-Wei Wang,
- Neng Gu,
- Saurabh Vishwas Joshi,
- Nazanin Farahpour,
- Zhiyuan Zhang,
- Andrew Zhai
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 5249–5259https://doi.org/10.1145/3580305.3599918Sequential models that encode user activity for next action prediction have become a popular design choice for building web-scale personalized recommendation systems. Traditional methods of sequential recommendation either utilize end-to-end learning on ...
- research-articleAugust 2023
Stationary Algorithmic Balancing For Dynamic Email Re-Ranking Problem
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 4527–4538https://doi.org/10.1145/3580305.3599909Email platforms need to generate personalized rankings of emails that satisfy user preferences, which may vary over time. We approach this as a recommendation problem based on three criteria: closeness (how relevant the sender and topic are to the user),...
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- research-articleAugust 2023
SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 3737–3749https://doi.org/10.1145/3580305.3599907We study the ability of transformer-based language models (LMs) to understand social media language. Social media (SM) language is distinct from standard written language, yet existing benchmarks fall short of capturing LM performance in this socially, ...
- research-articleAugust 2023
RLTP: Reinforcement Learning to Pace for Delayed Impression Modeling in Preloaded Ads
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 5204–5214https://doi.org/10.1145/3580305.3599900To increase brand awareness, many advertisers conclude contracts with advertising platforms to purchase traffic and deliver advertisements to target audiences. In a whole delivery period, advertisers desire a certain impression count for the ads, and ...
- research-articleAugust 2023
PIER: Permutation-Level Interest-Based End-to-End Re-ranking Framework in E-commerce
- Xiaowen Shi,
- Fan Yang,
- Ze Wang,
- Xiaoxu Wu,
- Muzhi Guan,
- Guogang Liao,
- Wang Yongkang,
- Xingxing Wang,
- Dong Wang
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 4823–4831https://doi.org/10.1145/3580305.3599886Re-ranking draws increased attention on both academics and industries, which rearranges the ranking list by modeling the mutual influence among items to better meet users' demands. Many existing re-ranking methods directly take the initial ranking list ...
- research-articleAugust 2023
PASS: Personalized Advertiser-aware Sponsored Search
- Zhoujin Tian,
- Chaozhuo Li,
- Zhiqiang Zuo,
- Zengxuan Wen,
- Lichao Sun,
- Xinyue Hu,
- Wen Zhang,
- Haizhen Huang,
- Senzhang Wang,
- Weiwei Deng,
- Xing Xie,
- Qi Zhang
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 4924–4936https://doi.org/10.1145/3580305.3599882The nucleus of online sponsored search systems lies in measuring the relevance between the search intents of users and the advertising purposes of advertisers. Existing conventional doublet-based (query-keyword) relevance models solely rely on short ...
- research-articleAugust 2023
Optimizing Airbnb Search Journey with Multi-task Learning
- Chun How Tan,
- Austin Chan,
- Malay Haldar,
- Jie Tang,
- Xin Liu,
- Mustafa Abdool,
- Huiji Gao,
- Liwei He,
- Sanjeev Katariya
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 4872–4881https://doi.org/10.1145/3580305.3599881At Airbnb, an online marketplace for stays and experiences, guests often spend weeks exploring and comparing multiple items before making a final reservation request. Each reservation request may then potentially be rejected or cancelled by the host ...
- research-articleAugust 2023
Off-Policy Learning-to-Bid with AuctionGym
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 4219–4228https://doi.org/10.1145/3580305.3599877Online advertising opportunities are sold through auctions, billions of times every day across the web. Advertisers who participate in those auctions need to decide on a bidding strategy: how much they are willing to bid for a given impression ...
- research-articleAugust 2023
Modelling Delayed Redemption with Importance Sampling and Pre-Redemption Engagement
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 3926–3936https://doi.org/10.1145/3580305.3599867Rewards-based programs are popular within e-commerce online stores, with the goal of providing serendipitous incentives to delight customers. These rewards (or incentives) could be in the form of cashback, free-shipping or discount coupons on purchases ...
- research-articleAugust 2023
M3PT: A Multi-Modal Model for POI Tagging
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 5382–5392https://doi.org/10.1145/3580305.3599862POI tagging aims to annotate a point of interest (POI) with some informative tags, which facilitates many services related to POIs, including search, recommendation, and so on. Most of the existing solutions neglect the significance of POI images and ...
- research-articleAugust 2023
Knowledge Based Prohibited Item Detection on Heterogeneous Risk Graphs
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 5260–5269https://doi.org/10.1145/3580305.3599852With the popularity of online shopping in recent years, various prohibited items are continuously attacking e-commerce portals. Searching and deleting such risk items online has played a fundamental role in protecting the health of e-commerce trades. To ...
- research-articleAugust 2023
Influence Maximization with Fairness at Scale
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 4046–4055https://doi.org/10.1145/3580305.3599847In this paper, we revisit the problem of influence maximization with fairness, which aims to select k influential nodes to maximise the spread of information in a network, while ensuring that selected sensitive user attributes (e.g., gender, location, ...
- research-articleAugust 2023
From Labels to Decisions: A Mapping-Aware Annotator Model
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 5404–5415https://doi.org/10.1145/3580305.3599828Online platforms regularly rely on human annotators to make real-time operational decisions for tasks such as content moderation. While crowdsourcing models have been proposed for aggregating noisy labels, they do not generalize well when annotators ...
- research-articleAugust 2023
Extreme Multi-Label Classification for Ad Targeting using Factorization Machines
- Martin Pavlovski,
- Srinath Ravindran,
- Djordje Gligorijevic,
- Shubham Agrawal,
- Ivan Stojkovic,
- Nelson Segura-Nunez,
- Jelena Gligorijevic
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 4705–4716https://doi.org/10.1145/3580305.3599822Applications involving Extreme Multi-Label Classification (XMLC) face several practical challenges with respect to scale, model size and prediction latency, while maintaining satisfactory predictive accuracy. In this paper, we propose a Multi-Label ...
- research-articleAugust 2023
Constrained Social Community Recommendation
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 5586–5596https://doi.org/10.1145/3580305.3599793In online social networks, users with similar interests tend to come together, forming social communities. Nowadays, user-defined communities become a prominent part of online social platforms as people who have joined such communities tend to be more ...
- research-articleAugust 2023
Capturing Conversion Rate Fluctuation during Sales Promotions: A Novel Historical Data Reuse Approach
- Zhangming Chan,
- Yu Zhang,
- Shuguang Han,
- Yong Bai,
- Xiang-Rong Sheng,
- Siyuan Lou,
- Jiacen Hu,
- Baolin Liu,
- Yuning Jiang,
- Jian Xu,
- Bo Zheng
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 3774–3784https://doi.org/10.1145/3580305.3599788Conversion rate (CVR) prediction is one of the core components in online recommender systems, and various approaches have been proposed to obtain accurate and well-calibrated CVR estimation. However, we observe that a well-trained CVR prediction model ...
- research-articleAugust 2023
BOSS: A Bilateral Occupational-Suitability-Aware Recommender System for Online Recruitment
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 4146–4155https://doi.org/10.1145/3580305.3599783With the rapid development of online recruitment platforms, a variety of emerging recommendation services have been witnessed for benefiting both job seekers and recruiters. While many researchers have studied the problem of reciprocal recommendation in ...