About Sound and Vision: CLEF Beyond Text Retrieval Tasks

2019 ◽  
pp. 307-329
Author(s):  
Gareth J. F. Jones
Keyword(s):  
Text Retrieval

Semantic-Preserving Metric Learning for Video-Text Retrieval

2021 ◽  
Author(s):  
Sungkwon Choo ◽  
Seong Jong Ha ◽  
Joonsoo Lee
Keyword(s):  
Metric Learning ◽  
Text Retrieval

Experiments with Language-based Aids in Information Retrieval Systems

1988 ◽  
Vol 11 (1-2) ◽  
pp. 33-46 ◽  
Author(s):  
Tove Fjeldvig ◽  
Anne Golden
Keyword(s):  
Information Retrieval ◽  
Text Retrieval ◽  
Considerable Improvement ◽  
Controlled Experiments ◽  
Compound Words ◽  
Search Results ◽  
Retrieval Systems ◽  
Complete Search ◽  
Information Retrieval Systems ◽  
Search Quality

The fact that a lexeme can appear in various forms causes problems in information retrieval. As a solution to this problem, we have developed methods for automatic root lemmatization, automatic truncation and automatic splitting of compound words. All the methods have as their basis a set of rules which contain information regarding inflected and derived forms of words – and not a dictionary. The methods have been tested on several collections of texts, and have produced very good results. By controlled experiments in text retrieval, we have studied the effects on search results. These results show that both the method of automatic root lemmatization and the method of automatic truncation make a considerable improvement on search quality. The experiments with splitting of compound words did not give quite the same improvement, however, but all the same this experiment showed that such a method could contribute to a richer and more complete search request.

scholarly journals Multi-keyword Cipher-text Retrieval Method for Smart Grid Edge Computing*

2021 ◽  
Vol 1754 (1) ◽  
pp. 012076
Author(s):  
Jing Zhu ◽  
Tao Wu ◽  
Jintao Li ◽  
Yanbin Liu ◽  
Qixin Jiang
Keyword(s):  
Smart Grid ◽  
Text Retrieval ◽  
Edge Computing ◽  
Retrieval Method ◽  
Cipher Text
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