Content-Based Filtering Recommendation in Abstract Search Using Neo4j

Content-Based Filtering Recommendation in Abstract Search Using Neo4j

© 2017 IEEE. In this work, we focus on development of a content search on report documents and recommendation on related document from search result. The main contribution of this work is to model document content into graph. Document-Keyword graph was created to represent the relationship between d...

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Main Authors: Ratsameetip Wita, Kawinwit Bubphachuen, Jakarin Chawachat
Format: Conference Proceeding
Published: 2018
Subjects:
Computer Science
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85053437856&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/62653
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Institution: Chiang Mai University
id th-cmuir.6653943832-62653
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spelling th-cmuir.6653943832-626532018-11-29T07:38:11Z Content-Based Filtering Recommendation in Abstract Search Using Neo4j Ratsameetip Wita Kawinwit Bubphachuen Jakarin Chawachat Computer Science © 2017 IEEE. In this work, we focus on development of a content search on report documents and recommendation on related document from search result. The main contribution of this work is to model document content into graph. Document-Keyword graph was created to represent the relationship between document and its features. The data were stored as a connected graph in Ne04j graph database. The graph were used to filter keyword co-occurrence documents in order to reduce search space. The performance of the proposed model was evaluated with accuracy 0.77. To improve the accuracy, the model can be extended with collecting user selection as collaborative feedback to the system, or extended with domain specific ontology to analyze the semantic relationship of the documents. 2018-11-29T07:38:11Z 2018-11-29T07:38:11Z 2018-08-21 Conference Proceeding 2-s2.0-85053437856 10.1109/ICSEC.2017.8443957 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85053437856&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/62653
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Computer Science
spellingShingle Computer Science
Ratsameetip Wita
Kawinwit Bubphachuen
Jakarin Chawachat
Content-Based Filtering Recommendation in Abstract Search Using Neo4j
description © 2017 IEEE. In this work, we focus on development of a content search on report documents and recommendation on related document from search result. The main contribution of this work is to model document content into graph. Document-Keyword graph was created to represent the relationship between document and its features. The data were stored as a connected graph in Ne04j graph database. The graph were used to filter keyword co-occurrence documents in order to reduce search space. The performance of the proposed model was evaluated with accuracy 0.77. To improve the accuracy, the model can be extended with collecting user selection as collaborative feedback to the system, or extended with domain specific ontology to analyze the semantic relationship of the documents.
format Conference Proceeding
author Ratsameetip Wita
Kawinwit Bubphachuen
Jakarin Chawachat
author_facet Ratsameetip Wita
Kawinwit Bubphachuen
Jakarin Chawachat
author_sort Ratsameetip Wita
title Content-Based Filtering Recommendation in Abstract Search Using Neo4j
title_short Content-Based Filtering Recommendation in Abstract Search Using Neo4j
title_full Content-Based Filtering Recommendation in Abstract Search Using Neo4j
title_fullStr Content-Based Filtering Recommendation in Abstract Search Using Neo4j
title_full_unstemmed Content-Based Filtering Recommendation in Abstract Search Using Neo4j
title_sort content-based filtering recommendation in abstract search using neo4j
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85053437856&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/62653
_version_ 1681425847215456256

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