NDLI: Expert evidence document recognition integrating relationship of expert

Content Provider	IEEE Xplore Digital Library
Author	Meng Wang Tao Shen Zhengtao Yu
Copyright Year	2013
Description	Author affiliation: Sch. of Inf. Eng. & Autom., Kunming Univ. of Sci. & Technol., Kunming, China (Meng Wang; Zhengtao Yu) \|\| Sch. of Mater. Sci. & Eng., Kunming Univ. of Sci. & Technol., Kunming, China (Tao Shen)
Abstract	Focus on the issue that the existing expert evidence document recognition method is not effective use of the relationship between experts, this paper proposed a method to recognize the expert evidence documents which integrate the feature of webpage content and the complex relationship between the experts. First of all, the method analyses characteristics of expert evidence document, to select Coauthors and organization as relationship feature, and then extracts feature values. Secondly, select 10130 expert evidence pages, and build data sets which integrate the feature values of and webpage content and the relationship, and then select different learning algorithms to build recognition model. Finally, experiment of expert evidence document recognition is carried out in the field of information processing. The experimental results shows that the proposed method achieves a good recognition effect. Using relationship can effectively improve the accuracy of the evidence document recognition. Its accuracy is improved by 4% compared to method using the page content feature recognition only.
Sponsorship	IEEE Control Syst. Soc.
Starting Page	997
Ending Page	1002
File Size	241719
Page Count	6
File Format	PDF
ISBN	9781467355339
e-ISBN	9781467355346
DOI	10.1109/CCDC.2013.6561069
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy Adaboost algorithm Expert evidence document recognition Training data Organizations Encyclopedias Feature extraction Content feature Relationship feature Classification algorithms Data mining
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Semi-supervised expert metadata extraction based on co-training style

Human Action Recognition Based on AdaBoost Algorithm for Feature Extraction

Keyframe extraction using AdaBoost

Document classification algorithm based on kernel logistic regression

Bio Named Entity Recognition Based on Co-training Algorithm

A classification of alternatively spliced cassette exons using AdaBoost-based algorithm

Using Naive Bayes with AdaBoost to Enhance Network Anomaly Intrusion Detection

An improved pedestrian detection algorithm based on Adaboost cascading stucture

Improving keyphrase extraction by using document topic information

Expert evidence document recognition integrating relationship of expert

Similar Documents

Semi-supervised expert metadata extraction based on co-training style

Human Action Recognition Based on AdaBoost Algorithm for Feature Extraction

Keyframe extraction using AdaBoost

Document classification algorithm based on kernel logistic regression

Bio Named Entity Recognition Based on Co-training Algorithm

A classification of alternatively spliced cassette exons using AdaBoost-based algorithm

Using Naive Bayes with AdaBoost to Enhance Network Anomaly Intrusion Detection

An improved pedestrian detection algorithm based on Adaboost cascading stucture

Improving keyphrase extraction by using document topic information

Expert evidence document recognition integrating relationship of expert