Cultural heritage is the root of national identities, and contributes to tourism, economics, industry, and business. Digital preservation of cultural heritage is therefore crucial, particularly in a form that is easily processable by machines. Available cultural heritage information on Web sources (e.g., Wikipedia) is presented in multiple formats, such as free-form text, lists, and tables. Such formats, however, lack structures and links to other information sources. The provision of cultural heritage information as a knowledge base, that is both structured and linked, would pave new ways for consuming such information. In this paper, we propose an approach to extract entities of cultural heritage from diverse formats (i.e., text, lists, and tables), and to construct a knowledge base of cultural heritage entities, called BudayaKB, using RDF data model that provides an integrated, format-independent view. Our extraction approach follows on the observation that cultural heritage entities are often written down either with common noun descriptors (e.g., Jiwa temple) or hypernym-hyponym sentence patterns (e.g., ... Acehnese traditional weapons such as Rencong...). We evaluate our approach to Indonesian Wikipedia, and achieve a precision of 84% for extracting Indonesian cultural heritage entities. The extracted entities are then imported and linked to the Wikidata KB, allowing greater interoperability of cultural heritage information. BudayaKB is openly available at https://budayakb.cs.ui.ac.id/.
{"title":"BudayaKB","authors":"Hadi Syah Putra, Rahmad Mahendra, Fariz Darari","doi":"10.1145/3326467.3326487","DOIUrl":"https://doi.org/10.1145/3326467.3326487","url":null,"abstract":"Cultural heritage is the root of national identities, and contributes to tourism, economics, industry, and business. Digital preservation of cultural heritage is therefore crucial, particularly in a form that is easily processable by machines. Available cultural heritage information on Web sources (e.g., Wikipedia) is presented in multiple formats, such as free-form text, lists, and tables. Such formats, however, lack structures and links to other information sources. The provision of cultural heritage information as a knowledge base, that is both structured and linked, would pave new ways for consuming such information. In this paper, we propose an approach to extract entities of cultural heritage from diverse formats (i.e., text, lists, and tables), and to construct a knowledge base of cultural heritage entities, called BudayaKB, using RDF data model that provides an integrated, format-independent view. Our extraction approach follows on the observation that cultural heritage entities are often written down either with common noun descriptors (e.g., Jiwa temple) or hypernym-hyponym sentence patterns (e.g., ... Acehnese traditional weapons such as Rencong...). We evaluate our approach to Indonesian Wikipedia, and achieve a precision of 84% for extracting Indonesian cultural heritage entities. The extracted entities are then imported and linked to the Wikidata KB, allowing greater interoperability of cultural heritage information. BudayaKB is openly available at https://budayakb.cs.ui.ac.id/.","PeriodicalId":112673,"journal":{"name":"Proceedings of the 9th International Conference on Web Intelligence, Mining and Semantics - WIMS2019","volume":"182 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123577410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we present the LODBookRec application. LODBookRec builds on top of Linked Open Data (LOD) knowledge about literature domain and provides information retrieval GUI to conveniently present this knowledge to the end users. As such, LODBookRec aims to contribute towards better utilization of LOD and provide a suitable platform for on-line evaluation of information retrieval methods, especially recommender systems. LODBookRec contains a basic search GUI and several recommendation methods, with the primary focus on item-based recommendations. The results of offline evaluation indicates that content-based recommendations utilizing attribute-based similarity of books provides best item-based recommendations w.r.t. recommendation relevance for both highly popular books as well as long-tail books. However, modification of the original algorithm via maximal margin relevance increases diversity of the recommended lists with a modest relevance penalties.
{"title":"LODBookRec","authors":"L. Malecek, Stepán Balcar, Ladislav Peška","doi":"10.1145/3326467.3326476","DOIUrl":"https://doi.org/10.1145/3326467.3326476","url":null,"abstract":"In this paper, we present the LODBookRec application. LODBookRec builds on top of Linked Open Data (LOD) knowledge about literature domain and provides information retrieval GUI to conveniently present this knowledge to the end users. As such, LODBookRec aims to contribute towards better utilization of LOD and provide a suitable platform for on-line evaluation of information retrieval methods, especially recommender systems. LODBookRec contains a basic search GUI and several recommendation methods, with the primary focus on item-based recommendations. The results of offline evaluation indicates that content-based recommendations utilizing attribute-based similarity of books provides best item-based recommendations w.r.t. recommendation relevance for both highly popular books as well as long-tail books. However, modification of the original algorithm via maximal margin relevance increases diversity of the recommended lists with a modest relevance penalties.","PeriodicalId":112673,"journal":{"name":"Proceedings of the 9th International Conference on Web Intelligence, Mining and Semantics - WIMS2019","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129666479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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