Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/5844
Full metadata record
DC FieldValueLanguage
dc.contributor.authorHakimov, S.-
dc.contributor.authorOto S. A.-
dc.contributor.authorDoğdu, Erdoğan-
dc.date.accessioned2021-09-11T15:20:20Z-
dc.date.available2021-09-11T15:20:20Z-
dc.date.issued2012en_US
dc.identifier.citation4th International Workshop on Semantic Web Information Management, SWIM'12, 20 May 2012 through 20 May 2012, Scottsdale, AZ, 90939en_US
dc.identifier.isbn9781450314466-
dc.identifier.urihttps://doi.org/10.1145/2237867.2237871-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/5844-
dc.description.abstractNamed Entity Recognition (NER) is a subtask of information extraction and aims to identify atomic entities in text that fall into predefined categories such as person, location, organization, etc. Recent efforts in NER try to extract entities and link them to linked data entities. Linked data is a term used for data resources that are created using semantic web standards such as DBpedia. There are a number of online tools that try to identify named entities in text and link them to linked data resources. Although one can use these tools via their APIs and web interfaces, they use different data resources and different techniques to identify named entities and not all of them reveal this information. One of the major tasks in NER is disambiguation that is identifying the right entity among a number of entities with the same names; for example "apple" standing for both "Apple, Inc." the company and the fruit. We developed a similar tool called NERSO, short for Named Entity Recognition Using Semantic Open Data, to automatically extract named entities, disambiguating and linking them to DBpedia entities. Our disambiguation method is based on constructing a graph of linked data entities and scoring them using a graph-based centrality algorithm. We evaluate our system by comparing its performance with two publicly available NER tools. The results show that NERSO performs better. © 2012 ACM.en_US
dc.description.sponsorshipACM Special Interest Group on Management of Data (SIGMOD)en_US
dc.language.isoenen_US
dc.relation.ispartofProceedings of the 4th International Workshop on Semantic Web Information Management, SWIM'12en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectcentrality algorithmsen_US
dc.subjectcloseness centralityen_US
dc.subjectDBpediaen_US
dc.subjectlinked dataen_US
dc.subjectnamed entityen_US
dc.subjectnamed entity disambiguationen_US
dc.subjectsemantic databasesen_US
dc.subjecttext annotationen_US
dc.titleNamed Entity Recognition and Disambiguation Using Linked Data and Graph-Based Centrality Scoringen_US
dc.typeConference Objecten_US
dc.departmentFaculties, Faculty of Engineering, Department of Computer Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümütr_TR
dc.identifier.scopus2-s2.0-84863477078en_US
dc.institutionauthorDoğdu, Erdoğan-
dc.identifier.doi10.1145/2237867.2237871-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.relation.conference4th International Workshop on Semantic Web Information Management, SWIM'12en_US
item.openairetypeConference Object-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

31
checked on Dec 21, 2024

Page view(s)

70
checked on Dec 23, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.