Filters








7 Hits in 1.2 sec

Catriple: Extracting Triples from Wikipedia Categories [chapter]

Qiaoling Liu, Kaifeng Xu, Lei Zhang, Haofen Wang, Yong Yu, Yue Pan
Lecture Notes in Computer Science  
Previous work has tried to extract such triples from Wikipedia infoboxes, article text and categories.  ...  This paper automatically extracts properties and triples from the less explored Wikipedia categories so as to achieve a wider article coverage with less manual effort.  ...  Conclusion This paper presents Catriple, a system which automatically extracts triples about Wikipedia articles and non-isa properties from Wikipedia categories.  ... 
doi:10.1007/978-3-540-89704-0_23 fatcat:kpdqt5ob5vd7defxdtdpu3lede

The Association Rule Mining System for Acquiring Knowledge of DBpedia from Wikipedia Categories

Jiseong Kim, Eun-Kyung Kim, Yousung Won, Sangha Nam, Key-Sun Choi
2015 International Semantic Web Conference  
In this regard, We propose a method that extracts RDF triples encoding concepts of entities or relations among entities from RDF triples encoding Wikipedia categories of each DBpedia entities using association  ...  In DBpedia KBs, they categorize their entities into Wikipedia categories using RDF triples.  ...  In 2008, Liu et al. suggested the approach Catriple [4] that analyze lexical patterns in expression of categories using NLP tools and use it to extract knowledge from categories.  ... 
dblp:conf/semweb/KimKWNC15 fatcat:oczmetxh7bahrkio6pycuotx24

Semantic Relationship Extraction and Ontology Building using Wikipedia: A Comprehensive Survey

Nora I. Al- Rajebah, Hend S. Al- Khalifa
2010 International Journal of Computer Applications  
Wikipedia is considered as one of the important knowledge sources that have been used to extract semantic relations due to its characteristics as a semi-structured knowledge source that would facilitate  ...  In this paper we will focus on the current state of this challenging field by discussing some of the recent studies about Wikipedia and semantic extraction and highlighting their main contributions and  ...  To evaluate the proposed method, 500 Catriple (Category Triples) triples were selected randomly to be judged by human judges, this yielded a precision ranged from 47.0% to 96.4%.  ... 
doi:10.5120/1661-2236 fatcat:54cgxwxatnawdbtp2reynusqo4

A hybrid method for detecting outdated information in Wikipedia infoboxes

Thong Tran, Tru H. Cao
2013 The 2013 RIVF International Conference on Computing & Communication Technologies - Research, Innovation, and Vision for Future (RIVF)  
In this paper, we propose a method to automatically detect outdated attribute values in Wikipedia infoboxes by using facts extracted from the general Web.  ...  Our method uses the pattern-based fact extraction approach. The patterns for fact extraction are automatically learned using a number of available seeds in related Wikipedia infoboxes.  ...  Catriple [6] was a system that automatically extracted triples from Wikipedia articles and non-isa properties from Wikipedia categories.  ... 
doi:10.1109/rivf.2013.6719874 dblp:conf/rivf/TranC13 fatcat:ih3y45lh4zb2zksf5kjgwmaapu

Automatic Detection of Outdated Information in Wikipedia Infoboxes

Thong Tran, Tru H. Cao
2013 Research in Computing Science  
In this paper, we propose a method to automatically detect outdated attribute values in Wikipedia infoboxes by using facts extracted from the general Web.  ...  Our method uses the pattern-based fact extraction approach. The patterns for fact extraction are automatically learned using a number of available seeds in related Wikipedia infoboxes.  ...  Catriple [6] was a system that automatically extracted triples from Wikipedia articles and non-isa properties from Wikipedia categories.  ... 
doi:10.13053/rcs-70-1-16 fatcat:ipdvvqveina7lnezewcr6u4rwq

An Evidence-Based Verification Approach to Extract Entities and Relations for Knowledge Base Population [chapter]

Naimdjon Takhirov, Fabien Duchateau, Trond Aalberg
2012 Lecture Notes in Computer Science  
This paper presents an approach to automatically extract entities and relationships from textual documents.  ...  The extracted entities and their expected relationships are verified using two evidence based techniques: classification and linking.  ...  For instance, Triplify has been designed to extract triples from Relational databases and expose them on LOD [2] while Catriple builds a store of triples from Wikipedia categories [11] .  ... 
doi:10.1007/978-3-642-35176-1_36 fatcat:sephbf73uvdfbeor4k3dzrvtum

Ontology learning from text

Wilson Wong, Wei Liu, Mohammed Bennamoun
2012 ACM Computing Surveys  
The explosion of textual information on the Read/Write Web coupled with the increasing demand for ontologies to power the Semantic Web have made (semi-)automatic ontology learning from text a very promising  ...  Similarly, developed a technique called Catriple for automatically extracting triples using Wikipedia's categorical system.  ...  Sentence parsers and syntactic rules are used to extract the explicit properties and values from the category names.  ... 
doi:10.1145/2333112.2333115 fatcat:4uo5bazvivh3fpbxj7yf4yoe2u