DocumentCode :
694830
Title :
Algorithm Research about Textual Case Retrieval Based on Topic Words
Author :
Lei Tang ; Ying Wang ; Yi Zhu ; Kunwang Tao ; Yong Feng ; Ying Guan
Author_Institution :
Sch. of Geomatics, Liaoning Tech. Univ., Fuxin, China
fYear :
2013
fDate :
7-8 Dec. 2013
Firstpage :
875
Lastpage :
880
Abstract :
Several shortages of Boolean retrieval, such as ignorance of the semantic relations among words and inability to rank the retrieval results in order of importance, are found by analyzing the essence of traditional text retrieval, in view of which an improvement of algorithm optimization based on topic words is proposed. Through enriching topic words to structure keywords library, the semantic distance and similarity of keywords are calculated on the basis of semantic retrieval framework. The improved algorithm is applied in the disaster case retrieval system at last, which retrieval results are then analyzed to detect performance. It is observed that the improved algorithm has a better improvement in retrieval both in precision rate and recall rate.
Keywords :
information retrieval; text analysis; Boolean retrieval; algorithm optimization; disaster case retrieval system; keyword similarity; precision rate; recall rate; semantic distance; semantic relations; semantic retrieval framework; textual case retrieval; topic words; Cognition; Earthquakes; Educational institutions; Electronic mail; Information retrieval; Libraries; Semantics; Boolean retrieval; improved algorithm; precision rate; recall rate; semantic distance; topic words;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Cloud Computing Companion (ISCC-C), 2013 International Conference on
Conference_Location :
Guangzhou
Type :
conf
DOI :
10.1109/ISCC-C.2013.35
Filename :
6973703
Link To Document :
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