• 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 106 matches

• 2023
• 
  Chaoquan Zhang:
  Reconstruction of 3D Building Models with Semantic Information Using Crowdsourcing Approaches. Norwegian University of Science and Technology, Trondheim, Norway, 2023
• 
  Michael Kölle:
  Forming a hybrid intelligence system by combining Active Learning and paid crowdsourcing for semantic 3D point cloud segmentation. University of Stuttgart, Germany, 2023
• 
  Mina Karimi, Mohammad Saadi Mesgari:
  Extracting Place Functionality From Crowdsourced Textual Data Using Semantic Space Modeling. IEEE Access 11: 129217-129229 (2023)
• 
  Brendan T. Johns:
  Computing word meanings by aggregating individualized distributional models: Wisdom of the crowds in lexical semantic memory. Cogn. Syst. Res. 80: 90-102 (2023)
• 
  Nana Hauwa Abdulsalam, Sufri Muhammad, Raihani Mohamed:
  A Review of Semantic-Based Reasoning Framework for Context-Aware Mobile-Crowdsourcing. CITA 2023: 94-99
• 
  Xinyu Liu, Tiancheng Sun, Diantian Fu, Zijue Li, Sheng Qian, Ruyue Meng, Mayank Kejriwal:
  Automatic Semantic Typing of Pet E-commerce Products Using Crowdsourced Reviews: An Experimental Study. KGSWC 2023: 151-167
• 
  Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Manas Gaur, Amit P. Sheth:
  IERL: Interpretable Ensemble Representation Learning - Combining CrowdSourced Knowledge and Distributed Semantic Representations. CoRR abs/2306.13865 (2023)
• 2022
• 
  Chao Li, Wennan Chai, Xiaohui Yang, Qingdang Li:
  Crowdsourcing-Based Indoor Semantic Map Construction and Localization Using Graph Optimization. Sensors 22(16): 6263 (2022)
• 
  Jincai Huang, Yunfei Zhang, Min Deng, Zhengbing He:
  Mining crowdsourced trajectory and geo-tagged data for spatial-semantic road map construction. Trans. GIS 26(2): 735-754 (2022)
• 
  Masaki Kobayashi, Hiromi Morita, Atsuyuki Morishima:
  Efficient Crowdsourcing for Semantic Segmentation Considering Human Cognitive Characteristics. HCI (37) 2022: 300-307
• 2021
• 
  Ja-Ryoung Choi, Soon-Bum Lim:
  Interactive E-Textbook Platform Based on Block Editing Model in Crowdsourcing E-Learning Environments. Int. J. Semantic Web Inf. Syst. 17(1): 50-66 (2021)
• 
  Anca Dumitrache, Oana Inel, Benjamin Timmermans, Carlos Martinez-Ortiz, Robert-Jan Sips, Lora Aroyo, Chris Welty:
  Empirical methodology for crowdsourcing ground truth. Semantic Web 12(3): 403-421 (2021)
• 
  Yonas Demeke Woldemariam:
  Expertise Detection in Crowdsourcing Forums Using the Composition of Latent Topics and Joint Syntactic-Semantic Cues. SN Comput. Sci. 2(6): 443 (2021)
• 
  Yao Sun, Ann Majchrzak, Arvind Malhotra:
  Understanding Collective Reflection in Crowdsourcing for Innovation: A Semantic Network Approach. HICSS 2021: 1-11
• 
  Michael Saxon, Xinyi Wang, William Yang Wang:
  Automatically Identifying Semantic Bias in Crowdsourced Natural Language Inference Datasets. CoRR abs/2112.09237 (2021)
• 2020
• 
  Qinyue Wu, Duankang Fu, Beijun Shen, Yuting Chen:
  Semantic Service Search in IT Crowdsourcing Platform: A Knowledge Graph-Based Approach. Int. J. Softw. Eng. Knowl. Eng. 30(6): 765-783 (2020)
• 
  Xing He, Hansi Zhang, Jiang Bian:
  User-centered design of a web-based crowdsourcing-integrated semantic text annotation tool for building a mental health knowledge base. J. Biomed. Informatics 110: 103571 (2020)
• 
  Nikolaos Lagos, Salah Ait-Mokhtar, Ioan Calapodescu:
  Point-Of-Interest Semantic Tag Completion in a Global Crowdsourced Search-and-Discovery Database. ECAI 2020: 2993-3000
• 
  Vincent Z. W. Mack, Qian Tang:
  Semantic and Network Evolution in Crowdsourced Idea Refinement. ICIS 2020
• 
  Veda Sunkara, Matthew Purri, Bertrand Le Saux, Jennifer Adams:
  Street to Cloud: Improving Flood Maps With Crowdsourcing and Semantic Segmentation. CoRR abs/2011.08010 (2020)
• 2019
• 
  Xin Hu, Jiangli Duan, Depeng Dang:
  Crowdsourcing-based semantic relation recognition for natural language questions over RDF data. Enterp. Inf. Syst. 13(7-8): 935-958 (2019)
• 
  Qingxian Pan, Hongbin Dong, Yingjie Wang, Zhipeng Cai, Lizong Zhang:
  Recommendation of Crowdsourcing Tasks Based on Word2vec Semantic Tags. Wirel. Commun. Mob. Comput. 2019: 2121850:1-2121850:10 (2019)
• 
  Srinivasa Raghavendra Bhuvan Gummidi, Torben Bach Pedersen, Xike Xie, Esteban Zimányi:
  Push-based Spatial Crowdsourcing for Enriching Semantic Tags in OpenStreetMap. SIGSPATIAL/GIS 2019: 532-535
• 
  Sheng Guo, Man-On Pun:
  Construction of Semantic-Rich Indoor Pathway Models from Crowdsourced Trajectories. ICC 2019: 1-6
• 
  Zhanpeng Wu, Yan Zhou, Di Wu, Yipeng Zhou, Jing Qin:
  Crowdsourced Time-Sync Video Recommendation via Semantic-Aware Neural Collaborative Filtering. ICWE 2019: 171-186
• 
  Thomas Nobel, Stijn Hoppenbrouwers, Jan Mark Pleijsant, Mats Ouborg:
  Word Meaning, Data Semantics, Crowdsourcing, and the BKM/A-Lex Approach. OTM Workshops 2019: 67-78
• 
  Duankang Fu, Shufan Zhou, Beijun Shen, Yuting Chen:
  Enhancing Semantic Search of Crowdsourcing IT Services using Knowledge Graph. SEKE 2019: 307-409
• 2018
• 
  Saman Koswatte, Kevin McDougall, Xiaoye Liu:
  Relevance Assessment of Crowdsourced Data (CSD) Using Semantics and Geographic Information Retrieval (GIR) Techniques. ISPRS Int. J. Geo Inf. 7(7): 256 (2018)
• 
  Evgeny A. Stepanov, Shammur Absar Chowdhury, Ali Orkan Bayer, Arindam Ghosh, Ioannis Klasinas, Marcos Calvo, Emilio Sanchis, Giuseppe Riccardi:
  Cross-language transfer of semantic annotation via targeted crowdsourcing: task design and evaluation. Lang. Resour. Evaluation 52(1): 341-364 (2018)
• 
  Maribel Acosta, Amrapali Zaveri, Elena Simperl, Dimitris Kontokostas, Fabian Flöck, Jens Lehmann:
  Detecting Linked Data quality issues via crowdsourcing: A DBpedia study. Semantic Web 9(3): 303-335 (2018)

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