Large-scale databases of proper names

被引:2
|
作者
Conley, P [1 ]
Burgess, C [1 ]
Hage, D [1 ]
机构
[1] Univ Calif Riverside, Dept Psychol, Riverside, CA 92521 USA
来源
关键词
D O I
10.3758/BF03207713
中图分类号
B841 [心理学研究方法];
学科分类号
040201 ;
摘要
Few tools for research in proper names have been available-specifically, there is no large-scale corpus of proper names. Two corpora of proper names were constructed, one based on U.S. phone book listings, the other derived from a database of Usenet text. Name frequencies from both corpora were compared with human subjects' reaction times (RTs) to the proper names in a naming task. Regression analysis showed that the Usenet frequencies contributed to predictions of human RT, whereas phone book frequencies did not. In addition, semantic neighborhood density measures derived from the HAL corpus were compared with the subjects' RTs and found to be a better predictor of RT than was frequency in either corpus. These new corpora are freely available on line for download. Potentials for these corpora range from using the names as stimuli in experiments to using the corpus data in software applications.
引用
收藏
页码:215 / 219
页数:5
相关论文
共 50 条
  • [31] Detecting and correcting misclassified sequences in the large-scale public databases
    Bagheri, Hamid
    Severin, Andrew J.
    Rajan, Hridesh
    BIOINFORMATICS, 2020, 36 (18) : 4699 - 4705
  • [32] Using large-scale databases to measure outcomes in critical care
    Pronovost, P
    Angus, DC
    CRITICAL CARE CLINICS, 1999, 15 (03) : 615 - +
  • [33] Managing large-scale and wide-distributed databases on the Internet
    Tao, JW
    CANADIAN JOURNAL OF INFORMATION AND LIBRARY SCIENCE-REVUE CANADIENNE DES SCIENCES DE L INFORMATION ET DE BIBLIOTHECONOMIE, 2000, 25 (01): : 44 - 45
  • [34] iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases
    Tan, Jian
    Zhang, Rui
    Zhang, Tieying
    Li, Feifei
    Chen, Jie
    Zheng, Qixing
    Zhang, Ping
    Qiao, Honglin
    Shi, Yue
    Cao, Wei
    PROCEEDINGS OF THE VLDB ENDOWMENT, 2019, 12 (10): : 1221 - 1234
  • [35] A Data Cleansing Method for Clustering Large-Scale Transaction Databases
    Loh, Woong-Kee
    Moon, Yang-Sae
    Kang, Jun-Gyu
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2010, E93D (11) : 3120 - 3123
  • [36] Indexing pictures by key objects for large-scale image databases
    Huang, PW
    PATTERN RECOGNITION, 1997, 30 (07) : 1229 - 1237
  • [37] Voter Registration Databases and MRP: Toward the Use of Large-Scale Databases in Public Opinion Research
    Ghitza, Yair
    Gelman, Andrew
    POLITICAL ANALYSIS, 2020, 28 (04) : 507 - 531
  • [38] Wavelet adaptive proper orthogonal decomposition for large-scale flow data
    Philipp Krah
    Thomas Engels
    Kai Schneider
    Julius Reiss
    Advances in Computational Mathematics, 2022, 48
  • [39] Distributed Proper Orthogonal Decomposition for Large-Scale Networked Dynamical Systems
    Kojima, Chiaki
    Kawasaki, Issei
    Moriyama, Satoshi
    Wada, Jun
    2013 EUROPEAN CONTROL CONFERENCE (ECC), 2013, : 3439 - 3445
  • [40] Wavelet adaptive proper orthogonal decomposition for large-scale flow data
    Krah, Philipp
    Engels, Thomas
    Schneider, Kai
    Reiss, Julius
    ADVANCES IN COMPUTATIONAL MATHEMATICS, 2022, 48 (02)