intergoA package for interleaving / multileaving ranking generation in go
Stars: ✭ 30 (-74.14%)
Knowledge GraphsA collection of research on knowledge graphs
Stars: ✭ 845 (+628.45%)
cs6101The Web IR / NLP Group (WING)'s public reading group at the National University of Singapore.
Stars: ✭ 17 (-85.34%)
Nlp Projectsword2vec, sentence2vec, machine reading comprehension, dialog system, text classification, pretrained language model (i.e., XLNet, BERT, ELMo, GPT), sequence labeling, information retrieval, information extraction (i.e., entity, relation and event extraction), knowledge graph, text generation, network embedding
Stars: ✭ 360 (+210.34%)
Tutorial Utilizing KgResources for Tutorial on "Utilizing Knowledge Graphs in Text-centric Information Retrieval"
Stars: ✭ 148 (+27.59%)
RecboleA unified, comprehensive and efficient recommendation library
Stars: ✭ 780 (+572.41%)
MixGCFMixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems, KDD2021
Stars: ✭ 73 (-37.07%)
WhySoMuchknowledge graph recommendation
Stars: ✭ 67 (-42.24%)
GNN-Recommender-SystemsAn index of recommendation algorithms that are based on Graph Neural Networks.
Stars: ✭ 505 (+335.34%)
visdial-gnnPyTorch code for Reasoning Visual Dialogs with Structural and Partial Observations
Stars: ✭ 39 (-66.38%)
ITOIntelligence Task Ontology (ITO)
Stars: ✭ 37 (-68.1%)
industry-eval-EAAn Industry Evaluation of Embedding-based Entity Alignment @ COLING'20
Stars: ✭ 19 (-83.62%)
Information-RetrievalInformation Retrieval algorithms developed in python. To follow the blog posts, click on the link:
Stars: ✭ 103 (-11.21%)
skywalkRcode for Gogleva et al manuscript
Stars: ✭ 28 (-75.86%)
TransCSource code and datasets of EMNLP2018 paper: "Differentiating Concepts and Instances for Knowledge Graph Embedding".
Stars: ✭ 75 (-35.34%)
JPQCIKM'21: JPQ substantially improves the efficiency of Dense Retrieval with 30x compression ratio, 10x CPU speedup and 2x GPU speedup.
Stars: ✭ 39 (-66.38%)
FCA-Map💠 Ontology matching system based on formal concept analysis
Stars: ✭ 25 (-78.45%)
PDNThe official PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf '21)
Stars: ✭ 44 (-62.07%)
RankyMcRankFaceHardened Fork of Ranklib learning to rank library
Stars: ✭ 41 (-64.66%)
DIGA library for graph deep learning research
Stars: ✭ 1,078 (+829.31%)
kozaData transformation framework for LinkML data models
Stars: ✭ 21 (-81.9%)
evildorkEvildork targeting your fiancee👁️
Stars: ✭ 46 (-60.34%)
WSDM2021 NSMImproving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signals. WSDM 2021.
Stars: ✭ 84 (-27.59%)
TIFUKNNkNN-based next-basket recommendation
Stars: ✭ 38 (-67.24%)
wsdm-digg-2020No description or website provided.
Stars: ✭ 15 (-87.07%)
luceneApache Lucene open-source search software
Stars: ✭ 1,009 (+769.83%)
cherche📑 Neural Search
Stars: ✭ 196 (+68.97%)
IEAJKECode and data for our paper "Iterative Entity Alignment via Joint Knowledge Embeddings"
Stars: ✭ 43 (-62.93%)
knowledge-graphGraph Data Visualization Demo| 图数据搜索可视化应用案例
Stars: ✭ 30 (-74.14%)
SDM-RDFizerAn Efficient RML-Compliant Engine for Knowledge Graph Construction
Stars: ✭ 68 (-41.38%)
autocompleteEfficient and effective query auto-completion in C++.
Stars: ✭ 28 (-75.86%)
ChineseStarsRelationship中国明星数据爬取。你甚至可以拿到互联网上所有的人之间的关系,接下来你可以自己发挥!基于这些数据,你可以完成更多有趣的事情。比如说社交网络分析,关系网络可视化,算法研究,和其他有意思的事情。Chinese star data crawling. You can even get all the people on the internet! Based on these data, you can do more interesting things. For example, social network analysis, relational network visualization, algorithm research, and other interesting things.
Stars: ✭ 26 (-77.59%)
seeSearch Engine in Erlang
Stars: ✭ 27 (-76.72%)
PaperMacheteA project that uses Binary Ninja and GRAKN.AI to perform static analysis on binary files with the goal of identifying bugs in software.
Stars: ✭ 49 (-57.76%)
ReFineOfficial code of "Towards Multi-Grained Explainability for Graph Neural Networks" (2021 NeurIPS)
Stars: ✭ 40 (-65.52%)
KGPool[ACL 2021] KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction
Stars: ✭ 33 (-71.55%)
information retrieval systemThe goal of this project is to implement a basic information retrieval system using Python, NLTK and GenSIM.
Stars: ✭ 25 (-78.45%)
staginSTAGIN: Spatio-Temporal Attention Graph Isomorphism Network
Stars: ✭ 34 (-70.69%)
CSV2RDFStreaming, transforming, SPARQL-based CSV to RDF converter. Apache license.
Stars: ✭ 48 (-58.62%)
KG4RecKnowledge-aware recommendation papers.
Stars: ✭ 76 (-34.48%)
JD2Skills-BERT-XMLCCode and Dataset for the Bhola et al. (2020) Retrieving Skills from Job Descriptions: A Language Model Based Extreme Multi-label Classification Framework
Stars: ✭ 33 (-71.55%)
GNNs-in-Network-NeuroscienceA review of papers proposing novel GNN methods with application to brain connectivity published in 2017-2020.
Stars: ✭ 92 (-20.69%)
typedbTypeDB: a strongly-typed database
Stars: ✭ 3,152 (+2617.24%)
obo-relationsRO is an ontology of relations for use with biological ontologies
Stars: ✭ 63 (-45.69%)
tika-similarityTika-Similarity uses the Tika-Python package (Python port of Apache Tika) to compute file similarity based on Metadata features.
Stars: ✭ 92 (-20.69%)
cognipyIn-memory Graph Database and Knowledge Graph with Natural Language Interface, compatible with Pandas
Stars: ✭ 31 (-73.28%)
Intention-Mining-Intention Mining in Social Networking. It Mines Emotions and polarity for the given keyword . For the keyword it searchers the twitter for the comments and analyzes the results for various events such as Election results, Sports prediction Movie ratings, Breaking news events such as demonetisation and many more. Bayes , Maximum Entropy and Hidde…
Stars: ✭ 19 (-83.62%)
MetagraphMetagraph是一款知识创作分享工具,不同于以往的知识创作平台,Metagraph提供了强大的内容关联能力。
Stars: ✭ 18 (-84.48%)
MStreamAnomaly Detection on Time-Evolving Streams in Real-time. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.
Stars: ✭ 68 (-41.38%)
NBFNetOfficial implementation of Neural Bellman-Ford Networks (NeurIPS 2021)
Stars: ✭ 106 (-8.62%)
lldaLabeled LDA in Python
Stars: ✭ 19 (-83.62%)
CoLAKECOLING'2020: CoLAKE: Contextualized Language and Knowledge Embedding
Stars: ✭ 86 (-25.86%)
SWDMSIGIR 2017: Embedding-based query expansion for weighted sequential dependence retrieval model
Stars: ✭ 35 (-69.83%)