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KDD2023 Hot Retrieval Papers Full List
rockingdingo 2023-09-01 #KDD2023 #recommendation #retrievalThis blog summarizes the latest research development of Retrieval papers published in KDD2023 conferences. This year there are total 8 papers related to Retrieval in KDD2023. Most of the authors' affiliations are top research institutes (Google Research, DeepMind, Meta FAIR) and universities (Stanford, Berkeley, MIT, CMU and others).
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ACL2023 Hot Retrieval Papers Full List
rockingdingo 2023-08-31 #nlp #ACL2023 #retrievalThis blog summarizes the latest research development of retrieval papers published in ACL2023 conferences. This year there are total 76 papers related to retrieval in ACL2023. Most of the authors' affiliations are top research institutes (Google Research, DeepMind, Meta FAIR) and universities (Stanford, Berkeley, MIT, CMU and others).
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Deep Candidate Generation (DeepMatch) Algorithm in recommendation
rockingdingo 2021-07-25 #deep candidate generation #deepmatch #recommendation #vector retrievalIn this post, we will talk about some real-world applications of deep candidates generation (vector-retrieval) models in the matching stage of recommendation scenario. Commercial recommendation system will recommend tens of millions of items to each user. And the recommendation process usually consists of two stages: The first stage is the candidate generation(matching) stage, a few hundred candidates are selected from the pool of all candidate items. The second stage is the ranking stage in which hundreds of items are ranked and sorted by the ranking score. Then the top rated items are displayed to users.
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