• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 76 matches

• 2021
• 
  Andrew M. Childs, Shih-Han Hung, Tongyang Li:
  Quantum query complexity with matrix-vector products. CoRR abs/2102.11349 (2021)
• 2020
• 
  Orestis Polychroniou, Kenneth A. Ross:
  VIP: A SIMD vectorized analytical query engine. VLDB J. 29(6): 1243-1261 (2020)
• 
  Hongyu Ren, Weihua Hu, Jure Leskovec:
  Query2box: Reasoning over Knowledge Graphs in Vector Space Using Box Embeddings. ICLR 2020
• 
  Timo Homburg, Steffen Staab, Daniel Janke:
  GeoSPARQL+: Syntax, Semantics and System for Integrated Querying of Graph, Raster and Vector Data. ISWC (1) 2020: 258-275
• 
  Tal Friedman, Guy Van den Broeck:
  Symbolic Querying of Vector Spaces: Probabilistic Databases Meets Relational Embeddings. UAI 2020: 1268-1277
• 
  Hongyu Ren, Weihua Hu, Jure Leskovec:
  Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddings. CoRR abs/2002.05969 (2020)
• 
  Tal Friedman, Guy Van den Broeck:
  Symbolic Querying of Vector Spaces: Probabilistic Databases Meets Relational Embeddings. CoRR abs/2002.10029 (2020)
• 
  Timo Homburg, Steffen Staab, Daniel Janke:
  GeoSPARQL+: Syntax, Semantics and System for Integrated Querying of Graph, Raster and Vector Data - Technical Report. CoRR abs/2009.05032 (2020)
• 2019
• 
  Dwaipayan Roy, Debasis Ganguly, Mandar Mitra, Gareth J. F. Jones:
  Estimating Gaussian mixture models in the local neighbourhood of embedded word vectors for query performance prediction. Inf. Process. Manag. 56(3): 1026-1045 (2019)
• 
  Orestis Polychroniou, Kenneth A. Ross:
  Towards Practical Vectorized Analytical Query Engines. DaMoN 2019: 10:1-10:7
• 
  Shanxiang Lyu, Zheng Wang, Bingo Wing-Kuen Ling, Jinming Wen:
  Enhanced Vector Perturbation Precoding Based on Adaptive Query Points. GLOBECOM 2019: 1-5
• 
  Xiaoming Sun, David P. Woodruff, Guang Yang, Jialin Zhang:
  Querying a Matrix Through Matrix-Vector Products. ICALP 2019: 94:1-94:16
• 
  Kento Watanabe, Masataka Goto:
  Query-by-Blending: A Music Exploration System Blending Latent Vector Representations of Lyric Word, Song Audio, and Artist. ISMIR 2019: 144-151
• 
  Xiaoming Sun, David P. Woodruff, Guang Yang, Jialin Zhang:
  Querying a Matrix through Matrix-Vector Products. CoRR abs/1906.05736 (2019)
• 2018
• 
  Hua Jiang, Junfeng Kang, Zhenhong Du, Feng Zhang, Xiangzhi Huang, Renyi Liu, Xuanting Zhang:
  Vector Spatial Big Data Storage and Optimized Query Based on the Multi-Level Hilbert Grid Index in HBase. Inf. 9(5): 116 (2018)
• 
  Wenzhuo Xue, Hui Li, Yanguo Peng, Jiangtao Cui, Yu Shi:
  Secure k Nearest Neighbors Query for High-Dimensional Vectors in Outsourced Environments. IEEE Trans. Big Data 4(4): 586-599 (2018)
• 
  Zhi Cai, Fujie Ren, Juncheng Chen, Zhiming Ding:
  Vector-Based Trajectory Storage and Query for Intelligent Transport System. IEEE Trans. Intell. Transp. Syst. 19(5): 1508-1519 (2018)
• 
  Kuan-Yu Chen, Shih-Hung Liu, Berlin Chen, Hsin-Min Wang:
  Essence Vector-Based Query Modeling for Spoken Document Retrieval. ICASSP 2018: 6274-6278
• 
  Michael Bloodgood:
  Support Vector Machine Active Learning Algorithms with Query-by-Committee Versus Closest-to-Hyperplane Selection. ICSC 2018: 148-155
• 
  Michael Bloodgood:
  Support Vector Machine Active Learning Algorithms with Query-by-Committee versus Closest-to-Hyperplane Selection. CoRR abs/1801.07875 (2018)
• 
  Md. Faisal Mahbub Chowdhury, Vijil Chenthamarakshan, Rishav Chakravarti, Alfio Massimiliano Gliozzo:
  Query Focused Variable Centroid Vectors for Passage Re-ranking in Semantic Search. CoRR abs/1804.08057 (2018)
• 
  William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec:
  Querying Complex Networks in Vector Space. CoRR abs/1806.01445 (2018)
• 2017
• 
  Nieves R. Brisaboa, Guillermo de Bernardo, Gilberto Gutiérrez, Miguel R. Luaces, José R. Paramá:
  Efficiently Querying Vector and Raster Data. Comput. J. 60(9): 1395-1413 (2017)
• 
  Youzhong Ma, Shijie Jia, Yongxin Zhang:
  A novel approach for high-dimensional vector similarity join query. Concurr. Comput. Pract. Exp. 29(5) (2017)
• 
  Hassan Aït-Kaci, Samir Amir:
  Classifying and querying very large taxonomies with bit-vector encoding. J. Intell. Inf. Syst. 48(1): 1-25 (2017)
• 
  Vitaly Feldman, Cristobal Guzman, Santosh S. Vempala:
  Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization. SODA 2017: 1265-1277
• 
  Tim Gubner, Peter A. Boncz:
  Exploring Query Compilation Strategies for JIT, Vectorization and SIMD. ADMS@VLDB 2017: 9-17
• 2016
• 
  Gheorghi Guzun, Guadalupe Canahuate:
  Hybrid query optimization for hard-to-compress bit-vectors. VLDB J. 25(3): 339-354 (2016)
• 
  Xiaohe Zhang, Yitong Wang, Zhaoliang Liu, Ling-Yu Duan:
  Selectively Aggregated Fisher Vectors of Query Video for Mobile Visual Search. BigMM 2016: 334-341
• 
  Eriks Sneiders:
  Text Retrieval by Term Co-occurrences in a Query-based Vector Space. COLING 2016: 2356-2365

skipping 46 more matches