NDLI: Parameter learning for multi-factors of entity answer extracting

Content Provider	IEEE Xplore Digital Library
Author	Huanyun Zong Zhengtao Yu Cunli Mao Junjie Zou Jianyi Guo
Copyright Year	2010
Description	Author affiliation: The School of Information Engineering and Automation, Kunming University of Science and Technology, China (Huanyun Zong; Zhengtao Yu; Cunli Mao; Junjie Zou; Jianyi Guo)
Abstract	Entity extraction involves multi-factors, and the different factor has an impact on the answer in varying degrees, this paper presents a machine learning approach to parameter learning for entity answer. Firstly, in view of characteristics of the Question Answering System (QA), we define three elements of the text score, passage score and entity score which influenced the answer extraction, also give the relevant computational method about them. Then collect 400 entity answers of product, person, and organization according to TREC2009 entity task requirements. With the help of search engines, retrieve related pages and calculate the score of the various factors related to the answer respectively. Thereafter compute the score of entity answers according to a linear combination of the various factors. Define an initial score to extract the entity answer and get a sorted list of answers. Finally, mark these entities answer to obtain the correct marked answers corpus, then build parameter learning model by the EM algorithm iterate gradually to find the optimal answer weight of different factors that influenced the answer extraction. We carried on the experiment in the TREC2009 entity task; it shows very good results for this method. The accuracy of entity answer has achieved 88.93%.
Starting Page	2478
Ending Page	2482
File Size	273126
Page Count	5
File Format	PDF
ISBN	9781424459315
e-ISBN	9781424459346
DOI	10.1109/FSKD.2010.5569794
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Context passage relevance Parameter estimation Data mining Training entity relevance Accuracy entity answer extraction Machine learning parameter estimation text relevance EM algorithm
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

Entity answer extraction of web table

Passage Extraction Using Subsequence-Based Query-Sensitive Maximum Cut

Automatic filtering algorithm for imbalanced classification

A Research on Multi-feature Word-Level Paraphrase Extracting System Based on Context

Bio Named Entity Recognition Based on Co-training Algorithm

An Algorithm of Extracting Classification Rule Based on Classified Concept Lattice

Relationship Extraction Tactics of Chinese Entity Based on Formal Concept Connectivity Distance

Cross-Validation EM Training for Robust Parameter Estimation

Sensitive Information Acquisition Based on Machine Learning

Parameter learning for multi-factors of entity answer extracting

Similar Documents

Entity answer extraction of web table

Passage Extraction Using Subsequence-Based Query-Sensitive Maximum Cut

Automatic filtering algorithm for imbalanced classification

A Research on Multi-feature Word-Level Paraphrase Extracting System Based on Context

Bio Named Entity Recognition Based on Co-training Algorithm

An Algorithm of Extracting Classification Rule Based on Classified Concept Lattice

Relationship Extraction Tactics of Chinese Entity Based on Formal Concept Connectivity Distance

Cross-Validation EM Training for Robust Parameter Estimation

Sensitive Information Acquisition Based on Machine Learning

Parameter learning for multi-factors of entity answer extracting