This is a table of type proper and their frequencies. Use it to search & browse the list to learn more about your study carrel.
| proper | frequency |
|---|---|
| IR | 118 |
| Sect | 103 |
| BM25 | 94 |
| Table | 86 |
| Fig | 84 |
| Eq | 77 |
| Retrieval | 68 |
| S | 65 |
| Lucene | 63 |
| Information | 60 |
| English | 60 |
| K | 52 |
| 51 | |
| COLTR | 51 |
| D | 49 |
| T | 48 |
| Bantu | 47 |
| BERT | 42 |
| i | 41 |
| DOI | 41 |
| TREC | 39 |
| Neural | 39 |
| TransRev | 37 |
| sha | 36 |
| Task | 33 |
| M | 32 |
| L | 31 |
| eRisk | 30 |
| C | 30 |
| F | 29 |
| VRSS | 29 |
| BC | 28 |
| LSTM | 27 |
| CNN | 27 |
| A | 27 |
| Wikipedia | 26 |
| Analysis | 26 |
| Network | 25 |
| LDA | 25 |
| dom | 24 |
| W | 24 |
| AUC | 23 |
| Amazon | 22 |
| Cond | 22 |
| Model | 22 |
| TF | 22 |
| corpus | 21 |
| IDF | 21 |
| DMP | 21 |
| Adam | 21 |
| tf | 20 |
| STM | 20 |
| OLTR | 20 |
| Anserini | 20 |
| Research | 19 |
| G | 19 |
| GCN | 18 |
| DBGD | 18 |
| ID | 18 |
| SlideImages | 18 |
| PRF | 18 |
| N | 18 |
| ∈ | 17 |
| ij | 17 |
| Q | 17 |
| Graph | 17 |
| Convolutional | 17 |
| CheckThat | 16 |
| CLEF | 16 |
| BiLSTM | 16 |
| E | 16 |
| LMOTE | 16 |
| Overview | 16 |
| α | 15 |
| ILP | 15 |
| IDNE | 15 |
| Evaluation | 15 |
| Cross | 15 |
| Γ | 15 |
| − | 14 |
| Runyankore | 14 |
| PDGD | 14 |
| Multimodal | 14 |
| Document | 14 |
| Data | 14 |
| CRF | 13 |
| Networks | 13 |
| BCs | 13 |
| Deep | 13 |
| ChEMU | 13 |
| schema | 13 |
| Explorer | 13 |
| Language | 13 |
| Semantic | 13 |
| Text | 13 |
| Arabic | 12 |
| Conference | 12 |
| DocFigure | 12 |
| Fang | 12 |
| GRU | 12 |
| Hierarchical | 12 |
| LMP | 12 |
| Latent | 12 |
| PMGD | 12 |
| SVM | 12 |
| Zhang | 12 |
| seq2seq | 12 |
| sign(S | 12 |
| DCSO | 11 |
| ImageNet | 11 |
| IC | 11 |
| Dataset | 11 |
| MT | 11 |
| DAKE | 11 |
| Common | 11 |
| ARI | 11 |
| ACC | 11 |
| MAP | 11 |
| Yelp | 11 |
| MeSH | 11 |
| Severity | 11 |
| θ | 11 |
| Stepwise | 11 |
| Social | 11 |
| MediaEval | 11 |
| Recipe | 11 |
| REUTERS | 11 |
| R | 11 |
| MaxRef | 10 |
| DKM | 10 |
| EWC3 | 10 |
| FISM | 10 |
| 10 | |
| Fan | 10 |
| GBP | 10 |
| HFT | 10 |
| LTR | 10 |
| Log | 10 |
| PIGD | 10 |
| Random | 10 |
| Search | 10 |
| VAE | 10 |
| Wiki | 10 |
| idf | 10 |
| max | 10 |
| NLP | 10 |
| rev | 10 |
| Management | 9 |
| Fisher | 9 |
| Knowledge | 9 |
| GVNR | 9 |
| French | 9 |
| CEE | 9 |
| European | 9 |
| EWC2 | 9 |
| ELP | 9 |
| Africa | 9 |
| Linear | 9 |
| CLTR | 9 |
| MaxScore | 9 |
| TADW | 9 |
| Precision | 9 |
| ≤ | 9 |
| | | 9 |
| U | 9 |
| Weebit | 9 |
| Suel | 9 |
| Sepedi | 9 |
| SMOTE | 9 |
| SD2C | 9 |
| Rep | 9 |
| Dirichlet | 8 |
| Means | 8 |
| Long | 8 |
| Logistic | 8 |
| Li | 8 |
| F1-score | 8 |
| BC2 | 8 |
| Ding | 8 |
| DeepRank | 8 |
| CrisisMMD | 8 |
| Bias | 8 |
| National | 8 |
| AB | 8 |
| NTCIR-12 | 8 |
| Mandarin | 8 |
| PageRank | 8 |
| WebQ | 8 |
| Prediction | 8 |
| resp | 8 |
| doms(W | 8 |
| df | 8 |
| Word | 8 |
| dl | 8 |
| Wand | 8 |
| VAR | 8 |
| STL | 8 |
| SIGIR | 8 |
| Robust | 8 |
| Recall@k | 8 |
| EWC1 | 7 |
| Layer | 7 |
| HSAPA | 7 |
| HBiLSTM | 7 |
| GloVe | 7 |
| G2 | 7 |
| Fund | 7 |
| Foundation | 7 |
| Attention | 7 |
| EER | 7 |
| EBM25 | 7 |
| DeepWalk | 7 |
| Cruzado | 7 |
| CoOccur | 7 |
| Castells | 7 |
| AGNEWS | 7 |
| Machine | 7 |
| Location | 7 |
| 7 | |
| Mises | 7 |
| Standards | 7 |
| NLIDB | 7 |
| 7 | |
| retrieval | 7 |
| bi | 7 |
| TaskRanker | 7 |
| TWA | 7 |
| TIMES | 7 |
| sw | 7 |
| Sanz | 7 |
| Readability | 7 |
| RCNN | 7 |
| Qatar | 7 |
| von | 7 |
| PubMed | 7 |
| PMC | 7 |
| SNE | 7 |
| Hubble | 6 |
| Embeddings | 6 |
| FV | 6 |
| Forest | 6 |
| Forum | 6 |
| GMM | 6 |
| HATT | 6 |
| KNRM | 6 |
| IPS | 6 |
| Joint | 6 |
| KM | 6 |
| LCD | 6 |
| LM | 6 |
| DCMM | 6 |
| Development | 6 |
| Cambridge | 6 |
| DBPEDIA | 6 |
| D. | 6 |
| Cora | 6 |
| Context | 6 |
| Collection | 6 |
| Coh | 6 |
| Clustering | 6 |
| Chen | 6 |
| MRR | 6 |
| CANE | 6 |
| Baseline | 6 |
| B | 6 |
| Avg | 6 |
| Algorithm | 6 |
| AGBR | 6 |
| LT | 6 |
| FCT | 6 |
| Media | 6 |
| disjunctively | 6 |
| Support | 6 |
| Term | 6 |
| Transformer | 6 |
| TripAdvisor | 6 |
| UMLS | 6 |
| Z | 6 |
| doc_id | 6 |
| Spanish | 6 |
| q1 | 6 |
| λ | 6 |
| π | 6 |
| σ | 6 |
| Medium | 6 |
| −1 | 6 |
| Story | 6 |
| metapath | 6 |
| Sim | 6 |
| Relevance | 6 |
| Net | 6 |
| Metrix | 6 |
| Sentiment | 6 |
| Query | 6 |
| RQ3 | 6 |
| Ranking | 6 |
| RQ2 | 6 |
| SDM | 6 |
| SFG | 6 |
| SQA | 6 |
| SQL | 6 |
| SVD | 6 |
| GAN | 5 |
| July | 5 |
| Gaussian | 5 |
| Gradient | 5 |
| HPA | 5 |
| HSA | 5 |
| Formula | 5 |
| Indri | 5 |
| Inductive | 5 |
| International | 5 |
| LEN | 5 |
| KP | 5 |
| Keyphrase | 5 |
| Kumar | 5 |
| LC | 5 |
| LODO | 5 |
| LSA | 5 |
| Label | 5 |
| MCN | 5 |
| Extraction | 5 |
| MEMIS | 5 |
| FastText | 5 |
| Automatic | 5 |
| Eqs | 5 |
| Bi | 5 |
| MTL | 5 |
| AE | 5 |
| AGS | 5 |
| Adamic | 5 |
| Adar | 5 |
| Alam | 5 |
| Align | 5 |
| Approach | 5 |
| Bayes | 5 |
| Bmw | 5 |
| EQE1 | 5 |
| CHEMDNER | 5 |
| CLNC | 5 |
| CNNs | 5 |
| Clinchant | 5 |
| Corpus | 5 |
| Counterfactual | 5 |
| DBP15 | 5 |
| Descent | 5 |
| Disease | 5 |
| MKL | 5 |
| RNN | 5 |
| Markov | 5 |
| YAHOO | 5 |
| Tangent | 5 |
| Technology | 5 |
| Track | 5 |
| Trotman | 5 |
| V | 5 |
| Variational | 5 |
| Wachsmuth | 5 |
| Web | 5 |
| Webis | 5 |
| Yahoo | 5 |
| Standard | 5 |
| cos | 5 |
| k−1 | 5 |
| len(v | 5 |
| listwise | 5 |
| microblogs | 5 |
| softmax | 5 |
| td | 5 |
| × | 5 |
| Matrix | 5 |
| Systems | 5 |
| Wu | 5 |
| Science | 5 |
| Probabilistic | 5 |
| Max | 5 |
| SS | 5 |
| Mining | 5 |
| Models | 5 |
| Mühleisen | 5 |
| NDC | 5 |
| Online | 5 |
| Ontology | 5 |
| P(T | 5 |
| PACRR | 5 |
| NE | 5 |
| Robertson | 5 |
| Processing | 5 |
| RDM | 5 |
| Rank | 5 |
| ReadNet | 5 |
| Recurrent | 5 |
| 5 | |
| Proceedings | 5 |
| SC | 5 |
| HATT+ | 4 |
| JSD | 4 |
| JAPE | 4 |
| Human | 4 |
| Horizon | 4 |
| ExpID | 4 |
| Graphs | 4 |
| Gov2 | 4 |
| Gini | 4 |
| Factorization | 4 |
| Lexicon | 4 |
| LSI | 4 |
| Ministry | 4 |
| Load | 4 |
| MCAT | 4 |
| MF | 4 |
| MLP | 4 |
| MS | 4 |
| MSE | 4 |
| Macdonald | 4 |
| March | 4 |
| Mercer | 4 |
| Mubarak | 4 |
| En | 4 |
| Exam | 4 |
| Applications | 4 |
| Elasticsearch | 4 |
| CLEF-2018 | 4 |
| NN | 4 |
| Allocation | 4 |
| Ar | 4 |
| Association | 4 |
| Average | 4 |
| BC1 | 4 |
| Balog | 4 |
| BioASQ | 4 |
| Bpref | 4 |
| CDF | 4 |
| CNSI | 4 |
| Egypt | 4 |
| CPE | 4 |
| Cascade | 4 |
| Center | 4 |
| Chinese | 4 |
| Council | 4 |
| Croft | 4 |
| Cypher | 4 |
| DRMM | 4 |
| Differentiable | 4 |
| EW | 4 |
| NDCG | 4 |
| Jelinek | 4 |
| NOA | 4 |
| TIVS | 4 |
| US | 4 |
| User | 4 |
| VMF | 4 |
| VSM | 4 |
| Vector | 4 |
| WEB10 | 4 |
| WSE | 4 |
| WSEs | 4 |
| Working | 4 |
| co(x | 4 |
| corp | 4 |
| c|q | 4 |
| ga | 4 |
| greek | 4 |
| i. | 4 |
| jth | 4 |
| lang | 4 |
| min | 4 |
| nDCG@100 | 4 |
| q. | 4 |
| rel(G | 4 |
| Δ | 4 |
| Natural | 4 |
| Translation | 4 |
| β | 4 |
| System | 4 |
| RCV2 | 4 |
| New | 4 |
| News | 4 |
| Office | 4 |
| OldDog | 4 |
| PMI | 4 |
| PR | 4 |
| PRH | 4 |
| QA | 4 |
| QLD | 4 |
| Question | 4 |
| Product | 4 |
| ROC | 4 |
| STR | 4 |
| Short | 4 |
| γ | 4 |
| SemEval | 4 |
| Schema | 4 |
| Saliency | 4 |
| Syst | 4 |
| Risk | 4 |
| Reuters | 4 |
| Recommender | 4 |
| Recall | 4 |
| Independence | 3 |
| K+1 | 3 |
| Jensen | 3 |
| Javier | 3 |
| Java | 3 |
| Italian | 3 |
| Intelligence | 3 |
| Intel | 3 |
| Integer | 3 |
| KEA | 3 |
| GB | 3 |
| Inception | 3 |
| IJCAI | 3 |
| Hindi | 3 |
| H | 3 |
| Graph2Gauss | 3 |
| Government | 3 |
| GitHub | 3 |
| GenomePT | 3 |
| Generation | 3 |
| GSRA | 3 |
| GR | 3 |
| Kincaid | 3 |
| KET | 3 |
| MHA | 3 |
| Kong | 3 |
| MSCOCO | 3 |
| G(Q | 3 |
| Multileaving | 3 |
| Multi | 3 |
| Modal | 3 |
| Mixture | 3 |
| MetaMap | 3 |
| Mention | 3 |
| Medical | 3 |
| MathIR | 3 |
| MSMARCO | 3 |
| MPCN | 3 |
| LCA | 3 |
| MIR | 3 |
| MARCO | 3 |
| Luganda | 3 |
| Liu | 3 |
| Linguistics | 3 |
| LibraryThing | 3 |
| Lee | 3 |
| Learning | 3 |
| Laplacian | 3 |
| Labs | 3 |
| G1 | 3 |
| Computational | 3 |
| Framework | 3 |
| Artificial | 3 |
| COCO | 3 |
| CLEF-2019 | 3 |
| CEUR | 3 |
| C(π | 3 |
| BioDeepRank | 3 |
| Berlin | 3 |
| Beauty | 3 |
| Bayesian | 3 |
| Based | 3 |
| Assessment | 3 |
| Argument | 3 |
| Ciência | 3 |
| Arg1 | 3 |
| Answering | 3 |
| Amsterdam | 3 |
| Allan | 3 |
| Algorithms | 3 |
| Actionable | 3 |
| Abstractive | 3 |
| AC4 | 3 |
| ABs | 3 |
| ): | 3 |
| CRM | 3 |
| Music | 3 |
| Fr | 3 |
| Doc | 3 |
| Flow | 3 |
| Flesch | 3 |
| FK | 3 |
| F1-Score | 3 |
| F-1 | 3 |
| Entity | 3 |
| Effectiveness | 3 |
| Education | 3 |
| E. | 3 |
| Domain | 3 |
| Discourse | 3 |
| Computer | 3 |
| Digital | 3 |
| DS | 3 |
| DL | 3 |
| DESM | 3 |
| DBPedia | 3 |
| DBOW | 3 |
| DAAT | 3 |
| Contact | 3 |
| Conditional | 3 |
| Computing | 3 |
| Multilingual | 3 |
| CCA | 3 |
| NER | 3 |
| Technologies | 3 |
| Zhai | 3 |
| Zamani | 3 |
| York | 3 |
| Yang | 3 |
| Xavier | 3 |
| X | 3 |
| World | 3 |
| Workshop | 3 |
| WordNet | 3 |
| Word2vec | 3 |
| WMD | 3 |
| Visual | 3 |
| Vanilla | 3 |
| VRNN | 3 |
| VIST | 3 |
| University | 3 |
| U.S. | 3 |
| Twenty | 3 |
| Topic | 3 |
| Times | 3 |
| Threshold | 3 |
| Theory | 3 |
| TextRank | 3 |
| ba | 3 |
| data.gov | 3 |
| desc | 3 |
| sup(AB | 3 |
| NI | 3 |
| ≥ | 3 |
| ← | 3 |
| • | 3 |
| λ(x | 3 |
| Σ | 3 |
| vector | 3 |
| txt | 3 |
| task | 3 |
| sup(BC | 3 |
| sepedi | 3 |
| e. | 3 |
| reqs | 3 |
| qj | 3 |
| q6 | 3 |
| q4 | 3 |
| nDCG@10 | 3 |
| multifield | 3 |
| log(1 | 3 |
| label | 3 |
| keyphrases | 3 |
| ej | 3 |
| Terrier | 3 |
| cBow | 3 |
| Suwaileh | 3 |
| Ranker | 3 |
| ROUGE | 3 |
| RCV1 | 3 |
| QLJM | 3 |
| Q2 | 3 |
| Q1 | 3 |
| Q&A | 3 |
| Python | 3 |
| PyTorch | 3 |
| Project | 3 |
| Principal | 3 |
| Plan | 3 |
| Perceptron | 3 |
| Patent | 3 |
| PL2 | 3 |
| P@k | 3 |
| P | 3 |
| Open | 3 |
| O(n | 3 |
| Nets | 3 |
| NUM | 3 |
| NS | 3 |
| Suggestion | 3 |
| NMF | 3 |
| Ra | 3 |
| Programming | 3 |
| Simple | 3 |
| SLIM | 3 |
| Solr | 3 |
| ReLU | 3 |
| Shannon | 3 |
| Shah | 3 |
| Setswana | 3 |
| SessionRanker | 3 |
| Self | 3 |
| SVal | 3 |
| SP | 3 |
| SMC-12 | 3 |
| Seed | 3 |
| SGNS | 3 |
| Review | 3 |
| RecipeQA | 3 |
| SGD | 3 |
| Reem | 3 |
| Regression | 3 |
| Recognition | 3 |
| Rm | 3 |
| S. | 3 |
| SERP | 3 |
| Grams | 2 |
| Generative | 2 |
| GeForce | 2 |
| Genomics | 2 |
| Gensim | 2 |
| Geolocation | 2 |
| Geonames | 2 |
| German | 2 |
| Ghahremanlou | 2 |
| Ghanem | 2 |
| Gibbs | 2 |
| Glove | 2 |
| Handbook | 2 |
| Grant | 2 |
| Graph2gauss | 2 |
| Greece | 2 |
| Grocery | 2 |
| Guido | 2 |
| Gulf | 2 |
| H@1 | 2 |
| HLT | 2 |
| HT | 2 |
| Hanbury | 2 |
| Ganguly | 2 |
| Gaussier | 2 |
| Exchange | 2 |
| Gaming | 2 |
| Federal | 2 |
| Haouari | 2 |
| Error | 2 |
| Expansion | 2 |
| Experimental | 2 |
| FCE | 2 |
| FEDER | 2 |
| FR | 2 |
| FUB | 2 |
| Faculty | 2 |
| Fasttext | 2 |
| Fatima | 2 |
| Feed | 2 |
| Galicia | 2 |
| Fields | 2 |
| Figs | 2 |
| Filtering | 2 |
| Flickr30k | 2 |
| Food-101 | 2 |
| Friedrich | 2 |
| Fusion | 2 |
| G(W | 2 |
| G. | 2 |
| GSRA5 | 2 |
| GTX | 2 |
| Hansen | 2 |
| Maram | 2 |
| Hasanain | 2 |
| MADIS | 2 |
| Lab | 2 |
| LamdaMART | 2 |
| Languages | 2 |
| Leekha | 2 |
| Lemur | 2 |
| Levantine | 2 |
| Lin | 2 |
| Lipani | 2 |
| Logic | 2 |
| Luca | 2 |
| M. | 2 |
| MEDLINE | 2 |
| Kwd | 2 |
| MLSR | 2 |
| MSI@100 | 2 |
| MSLR | 2 |
| Machines | 2 |
| Maghrebi | 2 |
| Maitree | 2 |
| Mallia | 2 |
| Enhanced | 2 |
| Markus | 2 |
| Martin | 2 |
| Math | 2 |
| LIBLINEAR | 2 |
| KvGR | 2 |
| Hassan | 2 |
| Incep | 2 |
| Head | 2 |
| Helpfulness | 2 |
| Hofstätter | 2 |
| I. | 2 |
| IASI | 2 |
| IBM | 2 |
| II | 2 |
| IT | 2 |
| Idf | 2 |
| Image | 2 |
| Images | 2 |
| Intelligent | 2 |
| Knowl.-Based | 2 |
| J. | 2 |
| JMARS | 2 |
| Jaccard | 2 |
| Jimmy | 2 |
| Joachims | 2 |
| Jobin | 2 |
| John | 2 |
| KG | 2 |
| Karoui | 2 |
| Kea | 2 |
| Kembhavi | 2 |
| Eric | 2 |
| CM | 2 |
| Engineering | 2 |
| Baselines | 2 |
| Assumption | 2 |
| Attn | 2 |
| Australian | 2 |
| Award | 2 |
| Aware | 2 |
| BBC | 2 |
| BIR | 2 |
| BM25F | 2 |
| BMBF | 2 |
| Bag | 2 |
| Bandit | 2 |
| Batch | 2 |
| CDIP | 2 |
| BeerAdvocate | 2 |
| Bert | 2 |
| Bidirectional | 2 |
| Bing | 2 |
| BioCreative | 2 |
| BioNLP | 2 |
| Biomedical | 2 |
| Bitesize | 2 |
| Block | 2 |
| Browsing | 2 |
| C. | 2 |
| Associated | 2 |
| Aspects | 2 |
| ArgumenText | 2 |
| Args | 2 |
| May | 2 |
| -VRSS | 2 |
| 8) | 2 |
| < | 2 |
| = | 2 |
| AAS | 2 |
| ACM | 2 |
| ALTA | 2 |
| API | 2 |
| AR | 2 |
| Acknowledgement | 2 |
| AdaDelta | 2 |
| Adrien | 2 |
| Adversarial | 2 |
| Afzal | 2 |
| Agarwal | 2 |
| Alberto | 2 |
| Alexa | 2 |
| Algorithmic | 2 |
| American | 2 |
| Application | 2 |
| Area | 2 |
| ArgM | 2 |
| CAE | 2 |
| CEUR-WS.org | 2 |
| Encoder | 2 |
| Disjunctively | 2 |
| David | 2 |
| De | 2 |
| Decomposition | 2 |
| Depression | 2 |
| Derivation | 2 |
| Description | 2 |
| Detection | 2 |
| Dimensionality | 2 |
| Disambiguation | 2 |
| Discounted | 2 |
| Disjunctive | 2 |
| Distance | 2 |
| CLAIRE | 2 |
| EC | 2 |
| EN | 2 |
| EPR | 2 |
| ERDE | 2 |
| ERDF | 2 |
| EWC | 2 |
| Economic | 2 |
| Efficiency | 2 |
| Elsayed | 2 |
| Elsevier | 2 |
| Emergency | 2 |
| Dataless | 2 |
| Das | 2 |
| DRD | 2 |
| DFR | 2 |
| CLIR | 2 |
| CLNC1 | 2 |
| CLS | 2 |
| CNR | 2 |
| COTLR | 2 |
| Canada | 2 |
| Carlo | 2 |
| Challenge | 2 |
| Chapter | 2 |
| ClaimBuster | 2 |
| CoFactor | 2 |
| Cohen | 2 |
| Commons | 2 |
| Community | 2 |
| Content | 2 |
| Core | 2 |
| Corollary | 2 |
| Correlation | 2 |
| Craig | 2 |
| Creative | 2 |
| Crossmodal | 2 |
| Czech | 2 |
| DCN | 2 |
| MaxID | 2 |
| IDEC | 2 |
| Mbakunda | 2 |
| document | 2 |
| Zheng | 2 |
| Zhou | 2 |
| Zlabinger | 2 |
| Zuccon | 2 |
| avdl | 2 |
| avg | 2 |
| bantu | 2 |
| bc | 2 |
| clust | 2 |
| dlossy | 2 |
| doc2vec | 2 |
| dsr | 2 |
| Wx | 2 |
| e.g | 2 |
| edn | 2 |
| eval | 2 |
| gensim | 2 |
| 2 | |
| gt | 2 |
| https://github.com/bioinformatics-ua/BioASQ | 2 |
| img | 2 |
| inv(link | 2 |
| isiZulu | 2 |
| ivory | 2 |
| Xeon | 2 |
| Wikimedia | 2 |
| k+1 | 2 |
| UPV | 2 |
| Tamer | 2 |
| Tecnologia | 2 |
| Tf | 2 |
| Tonellotto | 2 |
| Top | 2 |
| TransNets | 2 |
| Travel | 2 |
| Tree | 2 |
| Tweet | 2 |
| UID | 2 |
| UMAP | 2 |
| Union | 2 |
| Welch | 2 |
| Units | 2 |
| VGG-16 | 2 |
| Value | 2 |
| Vision | 2 |
| Viterbi | 2 |
| WK3l | 2 |
| War | 2 |
| Warm | 2 |
| WebQ. | 2 |
| Weekly | 2 |
| Wei | 2 |
| judged@20 | 2 |
| key | 2 |
| TREC-3 | 2 |
| yelp | 2 |
| tionV3 | 2 |
| top-3 | 2 |
| tweet | 2 |
| u. | 2 |
| ui | 2 |
| v0.6.0 | 2 |
| v3 | 2 |
| v4 | 2 |
| van | 2 |
| w.r.t | 2 |
| wikipedia | 2 |
| ×n | 2 |
| termremoval | 2 |
| δj | 2 |
| ζ(q | 2 |
| ν(G | 2 |
| ω | 2 |
| ↑↑ | 2 |
| ↑↓ | 2 |
| ∞ | 2 |
| ∧ | 2 |
| ∪ | 2 |
| Mean | 2 |
| ⊕ | 2 |
| ti | 2 |
| ta | 2 |
| kp20k | 2 |
| para | 2 |
| library | 2 |
| links(W | 2 |
| located_in | 2 |
| logs | 2 |
| matrixR | 2 |
| metapaths | 2 |
| mo | 2 |
| mv | 2 |
| nDCG@5 | 2 |
| p(i|x | 2 |
| p(x | 2 |
| prefix | 2 |
| susana.ladeiro | 2 |
| q3 | 2 |
| q5 | 2 |
| query | 2 |
| r+1 | 2 |
| rand | 2 |
| rec | 2 |
| revu | 2 |
| s(q | 2 |
| seeds(AB | 2 |
| subj | 2 |
| subtree(s | 2 |
| Tables | 2 |
| |x | 2 |
| TB | 2 |
| PCA | 2 |
| OPT | 2 |
| OR | 2 |
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| Operator | 2 |
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| Pairwise | 2 |
| Pan | 2 |
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| OOV | 2 |
| Notes | 2 |
| North | 2 |
| No | 2 |
| Metapath | 2 |
| Symptom | 2 |
| Metadata | 2 |
| Metapath2vec | 2 |
| Metric | 2 |
| Microsoft | 2 |
| Minimization | 2 |
| MonetDB | 2 |
| Morris | 2 |
| Mover | 2 |
| MovieLens | 2 |
| Multilayer | 2 |
| Multiview | 2 |
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| Sent | 2 |
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| Setup | 2 |
| Shi | 2 |
| Similarity | 2 |
| Skip | 2 |
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| Snippet | 2 |
| Socialism | 2 |
| South | 2 |
| Speech | 2 |
| Stack | 2 |
| Start | 2 |
| Stats | 2 |
| Study | 2 |
| Q. | 2 |
| Structure | 2 |
| Student | 2 |
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| StackExchange | 2 |
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