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20152023
most citedContrastive Learning of User Behavior Sequence for Context-Aware Document Ranking

30 citations · 96 across the 16 of their papers we have counts for

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Showing cs.IRShow all

6 papers · 1 filter

cs.IR20231 cited

Learning to Relate to Previous Turns in Conversational Search

Fengran Mo, Jian-Yun Nie, Kaiyu Huang +4

Conversational search allows a user to interact with a search system in multiple turns. A query is strongly dependent on the conversation context. An effective way to improve retri…

cs.IR2023

ConvGQR: Generative Query Reformulation for Conversational Search

Fengran Mo, Kelong Mao, Yutao Zhu +3

In conversational search, the user's real search intent for the current turn is dependent on the previous conversation history. It is challenging to determine a good search query f…

cs.IR20228 cited

From Easy to Hard: A Dual Curriculum Learning Framework for Context-Aware Document Ranking

Yutao Zhu, Jian-Yun Nie, Yixuan Su +3

Contextual information in search sessions is important for capturing users' search intents. Various approaches have been proposed to model user behavior sequences to improve docume…

cs.IR202130 cited

Contrastive Learning of User Behavior Sequence for Context-Aware Document Ranking

Yutao Zhu, Jian-Yun Nie, Zhicheng Dou +5

Context information in search sessions has proven to be useful for capturing user search intent. Existing studies explored user behavior sequences in sessions in different ways to…

cs.IR2021

The DELICES project: Indexing scientific literature through semantic expansion

Florian Boudin, Béatrice Daille, Evelyne Jacquey +1

Scientific digital libraries play a critical role in the development and dissemination of scientific literature. Despite dedicated search engines, retrieving relevant publications…

cs.IR2019

An End-to-End Neighborhood-based Interaction Model for Knowledge-enhanced Recommendation

Yanru Qu, Ting Bai, Weinan Zhang +2

This paper studies graph-based recommendation, where an interaction graph is constructed from historical records and is lever-aged to alleviate data sparsity and cold start problem…