Modeling the impact of short- and long-term behavior on search personalization
By Paul N. Bennett, Ryen W. White, Wei Chu, Susan T. Dumais, Peter Bailey, Fedor Borisyuk, Xiaoyuan Cui. Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2012
354 citations recorded by the source corpus.
Subfields: Information Systems, Information Systems and Management
View Paper: https://www.semanticscholar.org/paper/fbbf7af919fbcdbfd444945c2314fdffe79e608a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Systems
- Hamed Zamani
- W. Bruce Croft
- Nick Craswell
- Michael Bendersky
- Qingyao Ai
- Jiafeng Guo
- Liu Yang
- Ryen W. White
In Information Systems and Management
Citations in the corpus
- A Deep Look into Neural Ranking Models for Information Retrieval (2019, background): “• Long-term history: the historical information of the user’s queries that is often used for web search personalization [145, 146].”
- A Theoretical Framework for Conversational Search (2017, background): “In some systems the retrieval response is based only on the user’s most recent query, but other systems can take into account past queries and other context [4, 22].”
- Situational Context for Ranking in Personal Search (2017, background): “Previous work [5, 31, 34, 36, 43, 45, 46] often refers to query context as the information from the previous queries and their corresponding clickthrough data (i.e., short-and/or long-term search history).”
- Learning to personalize trending image search suggestion (2014, background): “The query log data in a search engine provide rich information of what users are interested [4, 24].”
- Exploring Time-Dependent Concerns about Pregnancy and Childbirth from Search Logs (2015, background): “Implications for the Design of Personalized Systems Temporal trends can present opportunities and challenges for personalized search [4,29].”
- Beliefs and biases in web search (2013, background): “A satisfied click has a subsequent dwell time of 30 or more seconds, or the last click in the session [5].”
- LaMP: When Large Language Models Meet Personalization (2023, background): “, 2022) and has also been extensively studied for search applications (Bennett et al., 2012; Dumais, 2016; Croft et al., 2001), in contexts ranging from query auto-”