DocumentCode :
260673
Title :
Information extraction based on probing algorithm with Bayesian approach
Author :
Davidson, J. Danie ; Jacob, I. Jeena ; Srinivasagam, K.G.
Author_Institution :
SCAD Coll. of Eng. & Tech, Tirunelveli, India
fYear :
2014
fDate :
27-28 Feb. 2014
Firstpage :
1
Lastpage :
4
Abstract :
Document Annotation is the task of adding metadata information in the document which is useful in information extraction. Document annotation has emerged as a different stream in data mining. Majority of algorithms are concentrated on query workload. This paper uses Probing algorithm with Bayesian approach which identifies the attribute based on query workload, text frequency and content of the previous text annotation such as content value. This method has been implemented in datasets that facilitates data annotation and prioritizes the values of the attributes by ranking scheme. Query cost is also low when compared to other approach. The experimental analysis shows a better performance while comparing with other methods because probability theory provides a principled foundation for such reasoning under uncertainty.
Keywords :
Bayes methods; data mining; meta data; query processing; text analysis; uncertainty handling; Bayesian approach; data annotation; data mining; document annotation; information extraction; metadata information; probability theory; probing algorithm; query cost; query workload; ranking scheme; reasoning; text annotation; text frequency; uncertainty; Algorithm design and analysis; Bayes methods; Educational institutions; Equations; Information retrieval; Mathematical model; Probes; Predicate; Probing; Query-cost;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Communication and Embedded Systems (ICICES), 2014 International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4799-3835-3
Type :
conf
DOI :
10.1109/ICICES.2014.7033761
Filename :
7033761
Link To Document :
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