sigir

There are 1 repository under sigir topic.

• chenchongthu / ENMF

  This is our implementation of ENMF: Efficient Neural Matrix Factorization (TOIS. 38, 2020). This also provides a fair evaluation of existing state-of-the-art recommendation models.

  deep-learningrecommender-systemefficient-algorithmrecommendationevaluationstate-of-the-artcollaborative-filteringreproducibilityreproducible-researchsigiricmllightgcnlcfnnbpokdddhcfneuripssrns
  Language:Python 150

• unsuthee / VariationalDeepSemanticHashing

  The original implementation of the models and experiments of Variational Deep Semantic Hashing paper (SIGIR 2017)

  sigirvariational-autoencoder
  Language:Python 55

• jinfengr / matrix-factorization-social-recommendation

  Probabilistic Matrix Factorization with Social Trust for Recommendation (Ma et al. SIGIR 2009)

  matrix-factorizationrecommender-systemsigirsocial-recommendationsocial-trust
  Language:Matlab 19

• zhengyima / paperlist_nlp_ir_rec_ai_conference

  2016-至今nlp/ir/recsys/ai相关顶会的论文清单paperlist列表含目录，方便直接搜索关键字。包括AAAI/ACL/EMNLP/IJCAI/SIGIR/CIKM/WSDM/WWW/NIPS/COLING

  ainlpmachine-learningdeep-learningrecommender-systempaperinformation-retrievalnatural-language-processingaaaiaclemnlpijcasigircikmwsdmwwwnipscolingartificial-intelligencenerual-network
  Language:Python 17

• mickeysjm / SetRank

  The source code, dataset, and evaluation scripts used for SetRank, published in SIGIR 2018

  information-retrievalelasticsearchranking-algorithmsigir
  Language:C 15

• unsuthee / SemanticHashingWeakSupervision

  The pyTorch implementation of two models described in Deep Semantic Text Hashing with Weak Supervision (SIGIR'18)

  semantichashingvariationalautoencoderweaksupervisionsigir
  Language:Python 15

• candidate-selection-tutorial-sigir2017 / candidate-selection-tutorial

  SIGIR 2017 Candidate Selection Tutorial (http://sigir.org/sigir2017/program/tutorials/#candidate)

  candidate-selectionsigir-2017sigir17sigir-17sigirtutorialrelevance
  Language:Python 14

• jjfiv / ltr2net

  Code and data for "Universal Approximation Functions for Fast Learning to Rank: Replacing Expensive Regression Forests with Simple Feed-Forward Networks"

  gov2learning-to-ranklambdamartpapersigirrandom-forestneural-network
  Language:Python 9

• guoyang9 / vqa-prior

  Implementation for our SIGIR 2019 paper --- Quantifying and Alleviating the Language Prior Problem in Visual Question Answering.

  vqapytorchlanguage-priorsigirvisual-question-answering
  Language:Python 6

• sjmoran / GRH

  Graph Regularised Hashing code

  hashing-algorithmmachine-learningecir2015image-processingimage-retrievalimage-classificationlocality-sensitive-hashingsigirliblinearlavrenkomorangrh
  Language:MATLAB 3

• webis-de / sigir20-sampling-bias-due-to-near-duplicates-in-learning-to-rank

  Sampling Bias Due to Near-Duplicates in Learning to Rank

  biasduplicatesinformation-retrievallearning-to-ranksigirsigir2020
  Language:Kotlin 2

• island99 / READ

  own made slides NLP, KG, or others

  nlppapersaclsigirijcaiknowledge-graph
  0

• Klajdi-Isteri / KGTERI_f

  This is the official repo of the dissertation "Exploiting Time and Content Information to Improve Collaborative and Knowledge-aware Recommendation" which involves the implementation of a new GNN model based on the approaches discussed in papers submitted/accepted at "SIGIR Conference on Research and Development in Information Retrieval".

  deep-learninggraph-neural-networkknowledge-graphrecommender-systemsigir
  Language:Python 0

• grill-lab / akbc-finance-kgs

  Paper and code accompanying AKBC 2022 Workshop

  economicsentitiesfinanceknowldge-graphretievalsearchsigirakbc
  Language:Shell