A Personalized Dense Retrieval Framework for Unified Information Access
A Personalized Dense Retrieval Framework for Unified Information Access
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DOI：
10.1145/3539618.3591626
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发表时间：
2023-04
期刊：
影响因子：
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通讯作者：
Hansi Zeng;Surya Kallumadi;Zaid Alibadi;Rodrigo Nogueira;Hamed Zamani
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文献类型：
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作者：
Hansi Zeng;Surya Kallumadi;Zaid Alibadi;Rodrigo Nogueira;Hamed Zamani
开发一个通用的模型，可以有效地和有效地响应广泛的信息访问请求-从检索到推荐到问答-一直是信息检索界的一个长期目标。本文认为，密集检索和近似最近邻搜索的最新发展所带来的灵活性，效率和有效性，为实现这一目标铺平了道路。我们开发了一个通用的和可扩展的密集检索框架，称为框架，可以处理广泛的（个性化）信息访问请求，如关键字搜索，查询的例子，和补充项目推荐。我们所提出的方法扩展了密集检索模型的能力，通过开发个性化的专注网络，将用户特定的偏好纳入特设检索任务。这允许更定制和准确的个性化信息访问体验。我们对真实世界的电子商务数据的实验表明，开发通用的信息访问模型的可行性，即使与专门为这些单独的信息访问任务开发的竞争性基线相比，也有显着的改进。这项工作为未来的探索开辟了许多基础研究方向。
Developing a universal model that can efficiently and effectively respond to a wide range of information access requests-from retrieval to recommendation to question answering---has been a long-lasting goal in the information retrieval community. This paper argues that the flexibility, efficiency, and effectiveness brought by the recent development in dense retrieval and approximate nearest neighbor search have smoothed the path towards achieving this goal. We develop a generic and extensible dense retrieval framework, called framework, that can handle a wide range of (personalized) information access requests, such as keyword search, query by example, and complementary item recommendation. Our proposed approach extends the capabilities of dense retrieval models for ad-hoc retrieval tasks by incorporating user-specific preferences through the development of a personalized attentive network. This allows for a more tailored and accurate personalized information access experience. Our experiments on real-world e-commerce data suggest the feasibility of developing universal information access models by demonstrating significant improvements even compared to competitive baselines specifically developed for each of these individual information access tasks. This work opens up a number of fundamental research directions for future exploration.