Time Context Model for Web Search based on Memory Activation Theory

被引:0
作者
Wang, Rifeng [1 ,2 ]
机构
[1] Beijing Univ Technol, Int WIC Inst, Beijing, Peoples R China
[2] Guangxi Univ Technol, Dept Comp Sci, Liuzhou, Peoples R China
来源
2011 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION AND INDUSTRIAL APPLICATION (ICIA2011), VOL III | 2011年
关键词
Memory activation theory; time context; Web search; vector space model; VECTOR-SPACE MODEL; INFORMATION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A the long term challenge of Web information retrieval is on the context area. Temporal feature is one of the elements of context that potentially significant to information retrieval but has not been considered currently. This paper proposed a time sensitive context vector model based on memory activation theory of human memory where activation of memory is decided by history use, weight of similar memory and correlation of current query. Human memory retrieval is time sensitive context search, which inspires a new web intelligent search model combined memory activation theory and vector space model. Algorithms of the new model are described in this paper and the temporal complexity and spatial complexity are also discussed. In relation to exiting models, the superiority of new model is in that it can retrieve authoritative and valuable information that users potentially want. This study is a tentative step toward intelligence of Web search.
引用
收藏
页码:45 / 48
页数:4
相关论文
共 17 条
[1]   Context-enabled learning in the human visual system [J].
Adini, Y ;
Sagi, D ;
Tsodyks, M .
NATURE, 2002, 415 (6873) :790-793
[2]  
Anderson J.R., 2000, OXFORD HDB MEMORY, P557
[3]   Human symbol manipulation within an integrated cognitive architecture [J].
Anderson, JR .
COGNITIVE SCIENCE, 2005, 29 (03) :313-341
[4]   An integrated theory of the mind [J].
Anderson, JR ;
Bothell, D ;
Byrne, MD ;
Douglass, S ;
Lebiere, C ;
Qin, YL .
PSYCHOLOGICAL REVIEW, 2004, 111 (04) :1036-1060
[5]  
ANDERSON JR, 1983, SCIENCE, V220, P25, DOI 10.1126/science.6828877
[6]  
[Anonymous], WORKSH HELD CTR INT
[7]   Exploiting hierarchical domain structure to compute similarity [J].
Ganesan, P ;
Garcia-Molina, H ;
Widom, J .
ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2003, 21 (01) :64-93
[8]   Improving category specific web search by learning query modifications [J].
Glover, EJ ;
Flake, GW ;
Lawrence, S ;
Birmingham, WP ;
Kruger, A ;
Giles, CL ;
Pennock, DM .
2001 SYMPOSIUM ON APPLICATIONS AND THE INTERNET, PROCEEDINGS, 2001, :23-31
[9]  
Huang L., 2000, SURVEY WEB INFORM RE
[10]  
Ingwersen P., 2005, SIGIR WORKSH