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Learning a Product Relevance Model from Click-Through Data in E-Commerce [article]

Shaowei Yao, Jiwei Tan, Xi Chen, Keping Yang, Rong Xiao, Hongbo Deng, Xiaojun Wan
<span title="2021-02-14">2021</span> <span class="release-stage" >pre-print</span>
In this paper, we propose a new relevance learning framework that concentrates on how to train a relevance model from the weak supervision of click-through data.  ...  Therefore, it is challenging but valuable to learn relevance models from click-through data.  ...  In this work, to mitigate the negative effect of the bias in e-commerce click-through data, we proposed a novel data-construction method to learn a robust relevance model from the more noisy click-through  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/3442381.3450129">doi:10.1145/3442381.3450129</a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2102.07098v1">arXiv:2102.07098v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jjfokqqrxnf5bgrny5cvlvj6zi">fatcat:jjfokqqrxnf5bgrny5cvlvj6zi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210217114526/https://arxiv.org/pdf/2102.07098v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/1f/47/1f4723490658c3ae8137125115e5d4d4deda4489.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/3442381.3450129"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2102.07098v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Neural IR Meets Graph Embedding: A Ranking Model for Product Search [article]

Yuan Zhang, Dong Wang, Yan Zhang
<span title="2019-01-24">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
a feature used in learning-to-rank frameworks.  ...  Extensive experiments on a real-world e-commerce dataset demonstrate significant improvement achieved by our proposed approach over multiple strong baselines both as an individual retrieval model and as  ...  automatically extracted from click-through data by GEPS.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1901.08286v1">arXiv:1901.08286v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/f37ls5e2wzbj7k34utr36j7jrm">fatcat:f37ls5e2wzbj7k34utr36j7jrm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200912161036/https://arxiv.org/pdf/1901.08286v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/09/a5/09a51f987771b3147bc8cb179a4563d5e2937fdd.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1901.08286v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

From Semantic Retrieval to Pairwise Ranking: Applying Deep Learning in E-commerce Search [article]

Rui Li, Yunjiang Jiang, Wenyun Yang, Guoyu Tang, Songlin Wang, Chaoyi Ma, Wei He, Xi Xiong, Yun Xiao, Eric Yihong Zhao
<span title="2021-03-24">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We introduce deep learning models to the two most important stages in product search at JD.com, one of the largest e-commerce platforms in the world.  ...  Specifically, we outline the design of a deep learning system that retrieves semantically relevant items to a query within milliseconds, and a pairwise deep re-ranking system, which learns subtle user  ...  Thus, instead of learning conversion rate, as most e-commerce ranking models do, we learn user preference between a pair of items for a given query.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2103.12982v1">arXiv:2103.12982v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3w4gbvnu4nestkjb2ta6g2idke">fatcat:3w4gbvnu4nestkjb2ta6g2idke</a> </span>
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Product engagement and identity signaling: The role of likes in social commerce for fashion products

Pei Xu, De Liu
<span title="">2018</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/achklm6s2rdkzlefw6cenfgf6i" style="color: black;">Information &amp; Management</a> </i> &nbsp;
A B S T R A C T Motivated by a lack of understanding of user engagement with identity-relevant products, we distinguish between two mechanisms by which existing likes affect subsequent engagement: observational  ...  By contrast, OL has a positive effect on clicks, and the effect diminishes as SI increases. We attribute our findings to identity signaling.  ...  From Polyvore, we gather data on handbags, which are widely deemed as an identity-relevant product category [8, 9] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.im.2018.04.001">doi:10.1016/j.im.2018.04.001</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2tkxdusz7na35d7zhrslypz64m">fatcat:2tkxdusz7na35d7zhrslypz64m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190222185627/http://pdfs.semanticscholar.org/41f8/27a34ea2627484cf92a4f8dd0d9106327941.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/41/f8/41f827a34ea2627484cf92a4f8dd0d9106327941.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.im.2018.04.001"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Ensemble Methods for Personalized E-Commerce Search Challenge at CIKM Cup 2016 [article]

Chen Wu, Ming Yan, Luo Si
<span title="2017-08-15">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Personalized search has been a hot research topic for many years and has been widely used in e-commerce.  ...  This paper describes our solution to tackle the challenge of personalized e-commerce search at CIKM Cup 2016.  ...  Statistic Features global statistic features In the e-commerce search scenario, products' historical click/sale conditions are quite important.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1708.04479v1">arXiv:1708.04479v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/y42a73sx2beufod4brtjwups4q">fatcat:y42a73sx2beufod4brtjwups4q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191020132713/https://arxiv.org/pdf/1708.04479v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/22/9f/229fc33d087b9c392d8998b1c9e67ad0294a481d.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1708.04479v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Mend The Learning Approach, Not the Data: Insights for Ranking E-Commerce Products [article]

Muhammad Umer Anwaar, Dmytro Rybalko, Martin Kleinsteuber
<span title="2020-07-09">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Traditional Learning to Rank (LTR) algorithms require relevance judgments on products. In E-Com, getting such judgments poses an immense challenge.  ...  To the best of our knowledge, this is the first work which examines effectiveness of CRM approach in learning ranking model from real-world logged data.  ...  Acknowledgments We would like to thank Alan Schelten, Till Brychcy and Rudolf Sailer for insightful discussions which helped in improving the quality of this work.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1907.10409v8">arXiv:1907.10409v8</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ccxgf4vrarfxrnj6n3gkoqjk5i">fatcat:ccxgf4vrarfxrnj6n3gkoqjk5i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200929051351/https://arxiv.org/pdf/1907.10409v8.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c0/4d/c04d73b04b48bb02b92c1a95fb8748157bcbbb86.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1907.10409v8" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Semantic Product Search for Matching Structured Product Catalogs in E-Commerce [article]

Jason Ingyu Choi, Surya Kallumadi, Bhaskar Mitra, Eugene Agichtein, Faizan Javed
<span title="2020-08-18">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Retrieving all semantically relevant products from the product catalog is an important problem in E-commerce.  ...  After training our models using user click logs from a well-known E-commerce platform, we show that our results provide useful insights for improving product search.  ...  In addition to the click logs dataset, we used a publicly available E-commerce dataset titled Product Search Relevance (PSR) dataset, which was released in 2016 as a Kaggle competition by an e-commerce  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2008.08180v1">arXiv:2008.08180v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oyoowx4q45bihdpvc3swtszyuy">fatcat:oyoowx4q45bihdpvc3swtszyuy</a> </span>
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Beyond Keywords and Relevance

Su Yan, Wei Lin, Tianshu Wu, Daorui Xiao, Xu Zheng, Bo Wu, Kaipeng Liu
<span title="">2018</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/s4hirppq3jalbopssw22crbwwa" style="color: black;">Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW &#39;18</a> </i> &nbsp;
To address these problems, we propose a novel ad retrieval framework beyond keywords and relevance in e-commerce sponsored search.  ...  Firstly, we employ historical ad click data to initialize a hierarchical network representing signals, keys and ads, in which personalized information is introduced.  ...  Specifically, in e-commerce sponsored search, the organic search results are trading products named "item", while the ads can be seen as a special kind of promotional products.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/3178876.3186172">doi:10.1145/3178876.3186172</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/www/YanLWXZWL18.html">dblp:conf/www/YanLWXZWL18</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/njj6rsodk5al7kux2ryyvoyyd4">fatcat:njj6rsodk5al7kux2ryyvoyyd4</a> </span>
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A unified Neural Network Approach to E-CommerceRelevance Learning [article]

Yunjiang Jiang, Yue Shang, Rui Li, Wen-Yun Yang, Guoyu Tang, Chaoyi Ma, Yun Xiao, Eric Zhao
<span title="2021-04-26">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Result relevance scoring is critical to e-commerce search user experience.  ...  We describe a highly-scalable feed-forward neural model to provide relevance score for (query, item) pairs, using only user query and item title as features, and both user click feedback as well as limited  ...  from label imbalance in the e-commerce search setting, where the click through labels are typically very sparse and have a highly skewed asymmetric distribution.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2104.12302v1">arXiv:2104.12302v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hm5ciew3jja4lochvs45etq5uq">fatcat:hm5ciew3jja4lochvs45etq5uq</a> </span>
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Neural Search: Learning Query and Product Representations in Fashion E-commerce [article]

Lakshya Kumar, Sagnik Sarkar
<span title="2021-07-17">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We approach this problem by learning low dimension representations for queries and product descriptions by leveraging user click-stream data as our main source of signal for product relevance.  ...  Therefore, showing the relevant products at the top is essential for the success of e-commerce platforms.  ...  Among different models, RoBERTa model act as a good baseline for serving the relevant products over fashion e-commerce given the user query.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2107.08291v1">arXiv:2107.08291v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/z3ycxfyw4be47ks5zvtbjlepk4">fatcat:z3ycxfyw4be47ks5zvtbjlepk4</a> </span>
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Learning to Rank Broad and Narrow Queries in E-Commerce [article]

Siddhartha Devapujula, Sagar Arora, Sumit Borar
<span title="2019-07-15">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this paper, we present a framework for building LETOR model for an e-commerce platform.  ...  While learning to Rank (LETOR) models have been extensively studied and have demonstrated efficacy in the context of web search; it is a relatively new research area to be explored in the e-commerce.  ...  INTRODUCTION Users on an e-commerce platform typically discover products through search, browsing categories or marketing campaigns.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1907.01549v2">arXiv:1907.01549v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jz63xaubvbc6xp2opcmgb5kwqu">fatcat:jz63xaubvbc6xp2opcmgb5kwqu</a> </span>
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On Application of Learning to Rank for E-Commerce Search

Shubhra Kanti Karmaker Santu, Parikshit Sondhi, ChengXiang Zhai
<span title="">2017</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ibcfmixrofb3piydwg5wvir3t4" style="color: black;">Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval - SIGIR &#39;17</a> </i> &nbsp;
Learning to Rank (LETOR) is a general effective strategy for optimizing search engines, and is thus also a key technology for E-Com search.  ...  In this paper, we discuss the practical challenges in applying learning to rank methods to E-Com search, including the challenges in feature representation, obtaining reliable relevance judgments, and  ...  What we found out is that even though the crowd-workers rated all these products with the ideal rating, i.e., 4, the actual number Table 6 : Variation in relevance judgments obtained from click data  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/3077136.3080838">doi:10.1145/3077136.3080838</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/sigir/SantuSZ17.html">dblp:conf/sigir/SantuSZ17</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qgijjtzauncepamqcs62ufqwle">fatcat:qgijjtzauncepamqcs62ufqwle</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190218144901/https://static.aminer.org/pdf/20170130/pdfs/sigir/wy6c1pacmre0zwbh49fhnangxmfkqd3l.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/7c/88/7c8822e4bff8eaa454a7a89bf13c443a16a85dd6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/3077136.3080838"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Towards Personalized and Semantic Retrieval: An End-to-End Solution for E-commerce Search via Embedding Learning [article]

Han Zhang, Songlin Wang, Kang Zhang, Zhiling Tang, Yunjiang Jiang, Yun Xiao, Weipeng Yan, Wen-Yun Yang
<span title="2020-06-05">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Two critical challenges stay in today's e-commerce search: how to retrieve items that are semantically relevant but not exact matching to query terms, and how to retrieve items that are more personalized  ...  Nowadays e-commerce search has become an integral part of many people's shopping routines.  ...  Our approach di ers from the previous methods in that we train a supervised model to directly optimize relevance metrics based on a large-scale data set with relevant signals, i.e., clicks.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2006.02282v3">arXiv:2006.02282v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ql3gtc5bwnb27p7l7vnmqgmpcm">fatcat:ql3gtc5bwnb27p7l7vnmqgmpcm</a> </span>
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A Regularised Intent Model for Discovering Multiple Intents in E-Commerce Tail Queries [chapter]

Subhadeep Maji, Priyank Patel, Bharat Thakarar, Mohit Kumar, Krishna Azad Tripathi
<span title="">2020</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
A substantial portion of the query volume for e-commerce search engines consists of infrequent queries and identifying user intent in such tail queries is critical in retrieving relevant products.  ...  Tail queries in e-commerce search tend to have multiple correct attribute labels for their tokens due to multiple valid matches in the product catalog.  ...  Performance in an Online A/B Experiment The intent inferred for a search query plays a major role in determining and retrieving the most relevant products for that query at Flipkart as is standard in e-commerce  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-030-45439-5_43">doi:10.1007/978-3-030-45439-5_43</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/475jep5ofneznhemg34btszn6a">fatcat:475jep5ofneznhemg34btszn6a</a> </span>
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Page-level Optimization of e-Commerce Item Recommendations [article]

Chieh Lo, Hongliang Yu, Xin Yin, Krutika Shetty, Changchen He, Kathy Hu, Justin Platz, Adam Ilardi, Sriganesh Madhvanath
<span title="2021-08-12">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The item details page (IDP) is a web page on an e-commerce website that provides information on a specific product or item listing.  ...  In our online A/B test, our framework improved click-through rate by 2.48% and purchase-through rate by 7.34% over a static configuration.  ...  We also demonstrated that such a system can be deployed at scale in production to serve millions of buyers on our e-commerce website responsively.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2108.05891v1">arXiv:2108.05891v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pthcwahr5vfsbflvanmtwy6rxy">fatcat:pthcwahr5vfsbflvanmtwy6rxy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210903122345/https://arxiv.org/pdf/2108.05891v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/7c/19/7c19ffe5f1c3fe19cde71617714e9c66ae2feec7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2108.05891v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>
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