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Entity Disambiguation with Freebase

Zhicheng Zheng, Xiance Si, Fangtao Li, Edward Y. Chang, Xiaoyan Zhu
2012 2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology  
Instead, we leverage two features of Freebase, namely the naturally disambiguated mention phrases (aka aliases) and the rich taxonomy, to perform disambiguation in an iterative manner.  ...  Specifically, we explore both generative and discriminative models for each iteration.  ...  taxonomy information as the RT methods.  ... 
doi:10.1109/wi-iat.2012.26 dblp:conf/webi/ZhengSLCZ12 fatcat:qpk4a5343baj7ovkxjunn3v7oq

Generating Information-Rich Taxonomy Using Wikipedia
Wikipedia を利用した上位下位関係の詳細化

Ichiro Yamada, Chikara Hashimoto, Jong-Hoon Oh, Kentaro Torisawa, Kow Kuroda, De Saeger Stijn, Masaaki Tsuchida, Jun'ichi Kazama
2012 Journal of Natural Language Processing  
In this paper, we propose a method of making (vague) hypernyms more specific ex- ploting Wikipedia.  ...  However, the informativeness of acquired hypernyms has not been sufficiently discussed.  ...  "Automatic Extraction of Hyponyms from Japanese Newspaper Using Lexico-syntactic Patterns."  ... 
doi:10.5715/jnlp.19.3 fatcat:7qhw4uhgxvejza3wfrdagpbibi

Building a Large-Scale Cross-Lingual Knowledge Base from Heterogeneous Online Wikis [chapter]

Mingyang Li, Yao Shi, Zhigang Wang, Yongbin Liu
2015 Lecture Notes in Computer Science  
Particularly, XLORE integrates four online wikis including English Wikipedia, Chinese Wikipedia, Baidu Baike and Hudong Baike to balance the knowledge volume in different languages, employs a link-discovery  ...  method to augment the cross-lingual links, and introduces a pruning approach to refine taxonomy.  ...  It extracts various kinds of structured information from Wikipedia and employs the multi-lingual characteristic of Wikipedia to generate 97 language versions of content.  ... 
doi:10.1007/978-3-319-25207-0_37 fatcat:n244qtdjibcplbwgznp5tcf63m

Comparing Taxonomies for Organising Collections of Documents

Samuel Fernando, Mark M. Hall, Eneko Agirre, Aitor Soroa, Paul D. Clough, Mark Stevenson
2012 International Conference on Computational Linguistics  
We use these taxonomies to organise items from a large online cultural heritage collection. We then present two human evaluations of the taxonomies.  ...  This paper examines four existing taxonomies that have been manually created, along with two methods for deriving taxonomies automatically from data items.  ...  Wikipedia Taxonomy Wikipedia Taxonomy (Ponzetto and Strube, 2011 ) is a taxonomy derived from Wikipedia categories.  ... 
dblp:conf/coling/FernandoHASCS12 fatcat:5753cgj6inhh5pnr6btau2l4v4

Large-Scale Taxonomy Mapping for Restructuring and Integrating Wikipedia

Simone Paolo Ponzetto, Roberto Navigli
2009 International Joint Conference on Artificial Intelligence  
We present a knowledge-rich methodology for disambiguating Wikipedia categories with WordNet synsets and using this semantic information to restructure a taxonomy automatically generated from the Wikipedia  ...  Besides, we assess these methods on automatically generated datasets and show that we are able to effectively enrich WordNet with a large number of instances from Wikipedia.  ...  Recent years have witnessed a considerable amount of work in information extraction to generate structured semantic content from Wikipedia.  ... 
dblp:conf/ijcai/PonzettoN09 fatcat:tmow6sowjvadpkqppsh3akmary

LINDEN

Wei Shen, Jianyong Wang, Ping Luo, Min Wang
2012 Proceedings of the 21st international conference on World Wide Web - WWW '12  
In this paper, we propose LINDEN 1 , a novel framework to link named entities in text with a knowledge base unifying Wikipedia and Word-Net, by leveraging the rich semantic knowledge embedded in the Wikipedia  ...  and the taxonomy of the knowledge base.  ...  The main contributions of this paper are summarized as follows. • We present LINDEN, a novel framework which leverages the rich semantic information derived from Wikipedia and the taxonomy of the knowledge  ... 
doi:10.1145/2187836.2187898 dblp:conf/www/ShenWLW12 fatcat:sshcibzw2zabbpockzdbzxud6i

Towards the Natural Ontology of Wikipedia

Andrea Giovanni Nuzzolese, Aldo Gangemi, Valentina Presutti, Paolo Ciancarini
2013 International Semantic Web Conference  
Hence, this ontology reflects the richness of terms used and agreed by the crowds, and can be updated periodically according to the evolution of Wikipedia.  ...  In this paper we present preliminary results on the extraction of ORA: the Natural Ontology of Wikipedia.  ...  Related work The DBpedia project [4] and YAGO [7] are the most relevant approaches at generating an ontology from semi-structured information in Wikipedia.  ... 
dblp:conf/semweb/NuzzoleseGPC13 fatcat:nnm4vq46abbpfabamar7z3cksi

XLORE2: Large-scale Cross-lingual Knowledge Graph Construction and Application

Hailong Jin, Chengjiang Li, Jing Zhang, Lei Hou, Juanzi Li, Peng Zhang
2019 Data Intelligence  
We present XLORE2, an extension of the XLORE that is built automatically from Wikipedia, Baidu Baike and Hudong Baike.  ...  Several projects construct KBs from Wikipedia, e.g., DBpedia [1], YAGO [2] and BabelNet [3]. Nevertheless, they have different focuses.  ...  The taxonomy directly derived from Wikipedia usually contains many mistakenly imported subClassOf and instanceOf relations.  ... 
doi:10.1162/dint_a_00003 dblp:journals/dint/JinLZHLZ19 fatcat:zdcq2gfyirc2ba4s6scxtytsna

Collaboratively built semi-structured content and Artificial Intelligence: The story so far

Eduard Hovy, Roberto Navigli, Simone Paolo Ponzetto
2013 Artificial Intelligence  
The results show that an open information extraction system can benefit greatly from a general-purpose, self-supervised extractor using dependency parse-level information (thus supporting related findings  ...  These include taxonomies, as well as their generalization to fully-structured knowledge models, i.e., ontologies.  ... 
doi:10.1016/j.artint.2012.10.002 fatcat:mwk5o254urb2dejsh7c224uu3q

Learning to Discover Subsumptions between Software Engineering Concepts in Wikipedia

Xiang Dong, Kai Chen, Jiangang Zhu, Beijun Shen
2016 Proceedings of the 28th International Conference on Software Engineering and Knowledge Engineering  
Wikipedia contains large-scale concepts and rich semantic information. A number of knowledge base construction projects such as WikiTaxonomy, DBpedia, and YAGO have acquired data from Wikipedia.  ...  Compared with the taxonomies which are extracted from general-purpose knowledge bases such as WikiTaxonomy, YAGO and Schema.org, our dataset has a larger scale in software engineering domain.  ...  Second, in order to get structural information from Wikipedia, we dump the Wikipedia XML file (https://dumps.wikimedia.org/enwiki/20150901/) and obtain a large-scale set which contains 5,027,000+ concepts  ... 
doi:10.18293/seke2016-021 dblp:conf/seke/DongCZS16 fatcat:f226amaa35eafndsk4yksktmhy

SEMANTIC SIMILARITY MEASUREMENT FOR MALAY WORDS USING WORDNET BAHASA AND WIKIPEDIA BAHASA MELAYU: ISSUES AND PROPOSED SOLUTIONS

Tuan Norhafizah Tuan Zakaria, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600 Selangor, Malaysia, Mohd Juzaiddin Ab Aziz, Mohd Rosmadi Mokhtar, Saadiyah Darus, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600 Selangor, Malaysia, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600 Selangor, Malaysia, Faculty of Social Sciences and Humanities, Universiti Kebangsaan Malaysia, 43600 Selangor,Malaysia
2020 International Journal of Software Engineering and Computer Systems  
WordNet Bahasa (WB) and Wikipedia Bahasa Melayu (WikiBM) are the example of lexical resources for Malay language. However, these lexical resources are still ongoing and limited semantic information.  ...  Knowledge-based lexical resources like WordNet and Wikipedia are useful for this task.  ...  Semantic information provided by WordNet Bahasa can be presented in semantic taxonomic form. Hypernym relations (IS-A) are used to generate semantic taxonomy.  ... 
doi:10.15282/ijsecs.6.1.2020.4.0067 fatcat:74rnf2kvonce5onhwseqnuhhm4

YAGO 4: A Reason-able Knowledge Base [chapter]

Thomas Pellissier Tanon, Gerhard Weikum, Fabian Suchanek
2020 Lecture Notes in Computer Science  
In this resource paper, we present its latest version, YAGO 4, which reconciles the rigorous typing and constraints of schema.org with the rich instance data of Wikidata.  ...  The main idea of YAGO was to harvest information about entities from the infoboxes and categories of Wikipedia, and to combine this data with an ontological backbone derived from classes in WordNet [4  ...  -Shapes: The SHACL constraints used to generate YAGO 4. Table 2 shows statistics for the three YAGO 4 variants, generated from the Wikidata N-Triples dump of November 25, 2019.  ... 
doi:10.1007/978-3-030-49461-2_34 fatcat:tawaoe3onbfljerzc6jq2iimfi

Taxonomy and clustering in collaborative systems: The case of the on-line encyclopedia Wikipedia

A. Capocci, F. Rao, G. Caldarelli
2007 Europhysics letters  
In this paper we investigate the nature and structure of the relation between imposed classifications and real clustering in a particular case of a scale-free network given by the on-line encyclopedia Wikipedia  ...  Regardless the statistically similar behaviour the two methods provide a rather different division of the articles, thereby signaling that the nature and presence of power laws is a general feature for  ...  Another well-known example of information network is the on-line, user-generated encyclopedias Wikipedia available at http://www.wikipedia.org in several languages.  ... 
doi:10.1209/0295-5075/81/28006 fatcat:55eo5gmirnfnrcucdhe7zlpzaq

Taxonomy induction based on a collaboratively built knowledge repository

Simone Paolo Ponzetto, Michael Strube
2011 Artificial Intelligence  
We propose to derive a taxonomy from the system of categories in Wikipedia.  ...  This allows us to generate a taxonomy from the Wikipedia category graph by performing the following task: for each pair of categories Subcat, Supercat where Subcat 3 is categorized into Supercat, decide  ...  The first author has been supported by a PhD scholarship from KTF (09.003.2004).  ... 
doi:10.1016/j.artint.2011.01.003 fatcat:lqpmsockpjaedbtwruvn6fsxxq

Coupling Wikipedia Categories with Wikidata Statements for Better Semantics

Houcemeddine Turki, Mohamed Ali Hadj Taieb, Mohamed Ben Aouicha
2021 International Semantic Web Conference  
is possible from a technical perspective thanks to the flexible data models of Wikipedia Categories and Wikidata statements and to the programmatic options provided by the Wikimedia Community.  ...  We also outline how such a combination can bring an added value to the development of Wikipedia Projects as well as to the enhancement of knowledge-based systems.  ...  ) of the other one and consequently to eliminate non-transitive relations from the Wikipedia Category Graph for the generation of an "is a" taxonomy that can be used to drive semantic applications.  ... 
dblp:conf/semweb/TurkiTA21 fatcat:fk2d6c2cr5ekxdqud7f22lq2de
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