Results 41 to 50 of about 372,511 (339)
A proposed conceptual framework for a representational approach to information retrieval [PDF]
SIGIR Forum, 2021 This paper outlines a conceptual framework for understanding recent developments in information retrieval and natural language processing that attempts to integrate dense and sparse retrieval methods. I propose a representational approach that breaks the
Jimmy J. Lin
semanticscholar +1 more source
Entity-Duet Neural Ranking: Understanding the Role of Knowledge Graph Semantics in Neural Information Retrieval [PDF]
Annual Meeting of the Association for Computational Linguistics, 2018 This paper presents the Entity-Duet Neural Ranking Model (EDRM), which introduces knowledge graphs to neural search systems. EDRM represents queries and documents by their words and entity annotations.
Zhenghao Liu +3 more
openalex +3 more sources
An Alternative Cross Entropy Loss for Learning-to-Rank
, 2021 Listwise learning-to-rank methods form a powerful class of ranking algorithms that are widely adopted in applications such as information retrieval. These algorithms learn to rank a set of items by optimizing a loss that is a function of the entire set --
Bruch, Sebastian
core +1 more source
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021 Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations. It aims to provide effective, reproducible, and easy-to-use first-stage retrieval in a multi-stage ranking architecture.
Jimmy J. Lin +6 more
semanticscholar +1 more source
An Adversarial Imitation Click Model for Information Retrieval [PDF]
The Web Conference, 2021 Modern information retrieval systems, including web search, ads placement, and recommender systems, typically rely on learning from user feedback. Click models, which study how users interact with a ranked list of items, provide a useful understanding of
Xinyi Dai +9 more
semanticscholar +1 more source
Dealing with Typos for BERT-based Passage Retrieval and Ranking [PDF]
Conference on Empirical Methods in Natural Language Processing, 2021 Passage retrieval and ranking is a key task in open-domain question answering and information retrieval. Current effective approaches mostly rely on pre-trained deep language model-based retrievers and rankers.
Shengyao Zhuang, G. Zuccon
semanticscholar +1 more source
Explainable Information Retrieval
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023 This tutorial presents explainable information retrieval (ExIR), an emerging area focused on fostering responsible and trustworthy deployment of machine learning systems in the context of information retrieval.
Avishek Anand +4 more
semanticscholar +1 more source
FAIR: Fairness‐aware information retrieval evaluation [PDF]
J. Assoc. Inf. Sci. Technol., 2021 With the emerging needs of creating fairness‐aware solutions for search and recommendation systems, a daunting challenge exists of evaluating such solutions.
Ruoyuan Gao, Yingqiang Ge, C. Shah
semanticscholar +1 more source
Research on Hybrid Retrieval-augmented Dual-tower Model [PDF]
Jisuanji kexueIn the vanguard of knowledge retrieval,particularly in scenarios involving large language models(LLMs),research emphasis has shifted toward employing pure vector retrieval techniques for efficient capture of pertinent information.This information is ...
GAO Hongkui, MA Ruixiang, BAO Qihao, XIA Shaojie, QU Chongxiao
doaj +1 more source
Re-ranking vehicle re-identification with orientation-guide query expansion
International Journal of Distributed Sensor Networks, 2022 Vehicle re-identification, which aims to retrieve information regarding a vehicle from different cameras with non-overlapping views, has recently attracted extensive attention in the field of computer vision owing to the development of smart cities. This
Xue Zhang +6 more
doaj +1 more source