{"product_id":"ieej-is14049","title":"Call For Paper Manager: Data Mapping and First Step to a CFP Ontology","description":"\u003cp\u003e\u003cstrong\u003eカテゴリ: \u003c\/strong\u003e研究会(論文単位)\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e論文No: \u003c\/strong\u003eIS14049\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eグループ名: \u003c\/strong\u003e【C】電子・情報・システム部門 情報システム研究会\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e発行日: \u003c\/strong\u003e2014\/11\/13\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eタイトル(英語): \u003c\/strong\u003eCall For Paper Manager: Data Mapping and First Step to a CFP Ontology\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e著者名: \u003c\/strong\u003eIssertial Laurent(大阪府立大学),辻 洋(大阪府立大学)\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e著者名(英語): \u003c\/strong\u003eIssertial Laurent(Osaka Prefecture University),Tsuji Hiroshi(Osaka Prefecture University)\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eキーワード: \u003c\/strong\u003etext mining|ontology|data management|call for paper\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e要約(日本語): \u003c\/strong\u003eThis paper introduces the addition of external ontology and creation of internal one to our Call For Paper Manager (extracting relevant data from CFP via text mining) in order to improve the quality of extracted data and lead to CFP Ontology. First, we take previously extracted locations and link them to DBPedia and GeoNames to collect additional information and disambiguate unknown type of location. Secondly, we extract topics from CFP and create a topic ontology based on CFP internal hierarchy to finally link it to external ontology namely DBPedia and the ACM Computing Classification System. Running experiements on a 300 CFP dataset, we find a location matching average of 85% on DBPedia with 60% unknown locations matched. For the topics, on the same dataset we obtain for extraction 0.89 for recall and 0.95 for precision with 8169 topics extracted, leading to the creation of a 5000 nodes for 7080 relations ontology.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e要約(英語): \u003c\/strong\u003eThis paper introduces the addition of external ontology and creation of internal one to our Call For Paper Manager (extracting relevant data from CFP via text mining) in order to improve the quality of extracted data and lead to CFP Ontology. First, we take previously extracted locations and link them to DBPedia and GeoNames to collect additional information and disambiguate unknown type of location. Secondly, we extract topics from CFP and create a topic ontology based on CFP internal hierarchy to finally link it to external ontology namely DBPedia and the ACM Computing Classification System. Running experiements on a 300 CFP dataset, we find a location matching average of 85% on DBPedia with 60% unknown locations matched. For the topics, on the same dataset we obtain for extraction 0.89 for recall and 0.95 for precision with 8169 topics extracted, leading to the creation of a 5000 nodes for 7080 relations ontology.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003e原稿種別: \u003c\/strong\u003e日本語\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003ePDFファイルサイズ: \u003c\/strong\u003e653 Kバイト\u003c\/p\u003e","brand":"IEEJ-PDF","offers":[{"title":"PDFダウンロード（一般価格330円\/会員価格220円） \/ A4 \/ 4","offer_id":46362826178799,"sku":"IEEJ-IS14049-PDF","price":330.0,"currency_code":"JPY","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0718\/9512\/2159\/files\/IEEJ-PDF_4f90308c-2da2-492a-9154-493f22e82e5f.png?v=1743640646","url":"https:\/\/ieej.bookpark.ne.jp\/products\/ieej-is14049","provider":"電気学会 電子図書館","version":"1.0","type":"link"}