Web Web [12] Web HTML HTML Web Web Web Web HTML Web Web Web Web Web Web Web Web Ducky[6][7] Ducky Web Web Ducky GUI GUI GUI Web 2 Ducky 3 GUI

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WebDB Forum 2015 Web Ducky GUI 1,a) 2,b) Web 2 Ducky Ducky Web URL CSS XML JSON CSV Ducky GUI GUI GUI Web Browser GUI for Rule Generation in Web Data Extraction System Ducky Kei Kanaoka 1,a) Motomichi Toyama 2,b) Abstract: To gain the benefit of invaluable data from World Wide Web, manual extraction or creation of web scraping programs may be necessary. But these processes can be tedious and complicated. To address these, we have proposed Ducky, which is a Web data extraction system including a web wrapper that extracts data from web sources and translates them into structured data based on a user-defined data extraction rules. Ducky is able to extract data flexibly from various structured web pages, remove noise from extracted data and integrate data distributed to multiple pages from different sites. In this paper, we propose the browser GUI of Ducky to help users to extract the data. It can operate intuitively by the actions such as clicking, pointing a cursor (mouse over) to an objective elements. These users actions are converted into data extraction rules in a configuration file. We hereby help users to extract the data by intuitive operations and reduce users burden to write the configuration file. 1. Web 2 1 Graduate School of Science and Technology, Keio University 2 Department of Information and Computer Science, Keio University a) kei@db.ics.keio.ac.jp b) toyama@ics.keio.ac.jp Web 2015 Information Processing Society of Japan 158

Web Web [12] Web HTML HTML Web Web Web Web HTML Web Web Web Web Web Web Web Web Ducky[6][7] Ducky Web Web Ducky GUI GUI GUI Web 2 Ducky 3 GUI 4 5 6 2. 2.1 Ducky 1 GUI Web Web URL 2 CSS (2.2.1) xml json csv { } "name" : "" 1 "author" : "" "frequency" : "" "format" : "" "scraping" : [{ }] 2 2.2 2.2.1 CSS \\ \\ \\ \\ \\ CSS Xpath HTML 3.com *1 HP URL HTML CSS div.unit li > a CSS HTML id, class, Ducky CSS 2 CSS Web Web DB *1 http://eiga.com/link/ 2015 Information Processing Society of Japan 159

HTML id class class.com div unit CSS CSS Web Web JavaScript (DOM) jquery W3Techs *2 2015 8 jquery Web 65.5 jquery CSS Web CSS 3 2.2.2 HTML scraping 4 1 GUI Web CSS selector. scraping ( 1 ) url selector URL HTML CSS HTML CSS *2 Web http://w3techs.com/ "scraping" : [{ "url" : " ", "selector" : " ", "data" : [{ "field" : " " "attr" : " " "find" : " ", "remove" : [" " " " ] "replace" : [[" " " "] ] }] "next" : { } }] 4 ( 2 ) data field attr find remove replace ( 3 ) next next URL url (1) DB next Web (3.2.3 ) 3. GUI GUI Web URL URL HTML GUI GUI (2.2.2) GUI Ameba *3 ( 5) 50 *4 *3 http://official.ameba.jp/ *4 http://official.ameba.jp/genrekana/kanatop.html 2015 Information Processing Society of Japan 160

1 scraping array url string URL selector string CSS data string ( ) field array attr string selector find string selector CSS blank remove array parentheses string replace array next object URL name url 6 ( 5 ) 3.1.3 URL ( 5 ) 6 Ameba 3.1 3.1.1 URL GUI 50 CSS 3.1.2 3.2 3.2.1 CSS GUI CSS CSS body class CSS 50 CSS 6 div.syllabarymdl > table > tbody > tr > td > a ( ) 3.2.2 alt ( 5 ) Web HTML 7 a img a 5 2015 Information Processing Society of Japan 161

図 5 ブラウザ GUI を用いたデータ抽出例 てクリックされた場合 その HTML 構造は図 7 のように なっているため img タグがもつ src 属性と alt 属性の値 親ノードである a タグの href 属性の値がポップアップに表 4. 評価 4.1 評価方法 今回提案したブラウザ GUI の有用性を評価するために 2 示される ユーザがポップアップのチェックボックスで選択したも つの実験を行った 1 つ目の実験では 30 の Web サイト のは 抽出対象として後にデータ抽出ルールに変換される を対象にブラウザ GUI を用いてデータ抽出を行った 2 つ 目の実験では 実験対象となる Web サイトを実験 1 の結 果から系統別に 2 つ選定し それぞれのサイトに対してブ ラウザ GUI を用いずにデータ抽出ルールを手書きで作成 してもらう場合と ブラウザ GUI を用いてデータ抽出を 行う場合に分けてユーザによる評価実験を行った なお 再現率と適合率は以下のように定義する 図 7 リンク付き画像の HTML 構造例 3.2.3 ページ遷移 ツールバー上の矢印ボタンがユーザによってクリックさ れた場合 選択されている要素の href 属性の値を取得し そのリンク先へページ遷移を行う これはデータ抽出ルー ルにおいて next フィールドを用いて表現される (図 6) 図 6 において 3 行目に存在する selector フィールド の値 div.syllabarymdl > table > tbody > tr > td > a 4.2 実験 1 は図 5 における 50 音順のリンクの位置を示す CSS セレク 4.2.1 結果および考察 タである ここで選択されたのは a タグであり href 属性 今回対象とした 30 の Web サイトのうち 23 の Web サ を持つ その値である URL が次の next フィールドにお イトからのデータ抽出に関するデータを表 2 に示す 表 2 ける url フィールドの値として用いられる (2.2.2) つ に記載したサイトのうち SONY 商品カテゴリー一覧*5 を まり あ から わ までの URL 全てにリクエストを送り 除き 再現率と適合率が 100%のデータを得ることが出来 その遷移先のページにおいて芸能人の名前とそのブログの た 以下 SONY 商品カテゴリー一覧に関して考察を行 URL を取得するといった処理を行う このように next う フィールドは遷移先の Web ページが同一のテンプレート SONY 商品カテゴリー一覧におけるデータ抽出の流れ で生成されている Web ページに対して それらの情報を は次のようになる 商品カテゴリー一覧から計 52 のカテ 抽出 統合することを可能にする ゴリーページへのリンクをクリックし ページ遷移する *5 2015 Information Processing Society of Japan http://www.sony.jp/products menu.html 162

*6 52 36 4 2 SONY SONY 36 7 *7 Javascript Web Ducky Web GUI Web 4.3 2 Web 1 2 * 2.com ( 1 ) 1 Ameba ( 2) Web Web GUI ( A) GUI ( B) ( ) GUI URL Web HTML CSS Javascript ( ) HTML *6 1 http://www.sony.jp/bravia/ *7 http://www.pokemon.jp/zukan/ CSS ( ) 3 6 GUI GUI CSS Google Chrome Web CSS 4.3.1 GUI 8 8 GUI GUI GUI HTML GUI 3 3 2 Web 2 100 GUI CSS 100 GUI 2 100 2 1 3 1 2 A B A B 1 66.6 64.5 100 100 45 41.6 100 83.3 2 100 92.3 - - 68.5 62.1 100 100 3 100 93 - - 100 80.1 - - 4 100 100 - - 100 90.2 - - 5 - - - - 100 100 - - 2015 Information Processing Society of Japan 163

2 Web ( ).com 1 - - - 2 549 FC Barcelona 1 - - - 3 26 EXILE HP 1 - - - 3 14 1 - - - 2 100 SKE48 HP 1 - - - 4 71 HP 4 - - 2 1136 1 - - 2 94 1 - - 4 73 1 (1) 6-2 83 NMB48 HP 1 - - 3 65 Ameba 1 (1) 44-3 11774 46 HP 1 - - 3 32 SAMURAI JAPAN 1 - - 6 12 DeNA 5 - - 4 90 1 - - 5 104 2-3 92 1-3 115 SAMURAI BLUE 1-5 51 HP 1-2 1634 1 (1) 5 6 170 21-2 3551 1 (1) 5 6 85 SONY 1 (3) 52 - - 3 238 URL HTML OXPath [4][11] Xpath DEiXTo [8] GUI 8 5. Web [12] Web Web XML Web 1 (semi-automatic) 2 (automatic) Zhang [13] Adelberg NoDoSE [1] XML Kushmerick[9] Kushmerick Chang [3] Chang IEPAD HTML IEPAD HTML HTML IEPAD 2015 Information Processing Society of Japan 164

URL Web Web [2] [5] GUI [10] URL OXPath[4] Web OXPath Web Web 6. Ducky GUI GUI Web 2 1 GUI CSS 2 GUI Web Web Web the 10th International Conference on World Wide Web, WWW 01, pages 681 688, New York, NY, USA, 2001. ACM. [4] Tim Furche, Georg Gottlob, Giovanni Grasso, Christian Schallhart, and Andrew Sellers. Oxpath: A language for scalable data extraction, automation, and crawling on the deep web. The VLDB Journal, 22(1):47 72, February 2013. [5] Matthias Geel, Timothy Church, and Moira C. Norrie. Sift: An end-user tool for gathering web content on the go. In Proceedings of the 2012 ACM Symposium on Document Engineering, DocEng 12, pages 181 190, New York, NY, USA, 2012. ACM. [6] Kei Kanaoka, Yotaro Fujii, and Motomichi Toyama. Ducky: A data extraction system for various structured web documents. In Proceedings of the 18th International Database Engineering & Applications Symposium, IDEAS 14, pages 342 347, New York, NY, USA, 2014. ACM. [7] Kei Kanaoka and Motomichi Toyama. Effective web data extraction with ducky. In Proceedings of the 19th International Database Engineering & Applications Symposium, IDEAS 15, pages 212 213, New York, NY, USA, 2014. ACM. [8] Fotios Kokkoras, Konstantinos Ntonas, and Nick Bassiliades. Deixto: A web data extraction suite. In Proceedings of the 6th Balkan Conference in Informatics, BCI 13, pages 9 12, New York, NY, USA, 2013. ACM. [9] Nicholas Kushmerick. Wrapper induction: Efficiency and expressiveness. Artif. Intell., 118(1-2):15 68, April 2000. [10] Tiezheng Nie, Zhenhua Wang, Yue Kou, and Rui Zhang. Crawling result pages for data extraction based on url classification. In Proceedings of the 2010 Seventh Web Information Systems and Applications Conference, WISA 10, pages 79 84, Washington, DC, USA, 2010. IEEE Computer Society. [11] Andrew Jon Sellers, Tim Furche, Georg Gottlob, Giovanni Grasso, and Christian Schallhart. Oxpath: Little language, little memory, great value. In Proceedings of the 20th International Conference Companion on World Wide Web, WWW 11, pages 261 264, New York, NY, USA, 2011. ACM. [12] H.A. Sleiman and R. Corchuelo. A survey on region extractors from web documents. Knowledge and Data Engineering, IEEE Transactions on, 25(9):1960 1981, September 2013. [13] Suzhi Zhang and Peizhong Shi. An efficient wrapper for web data extraction and its application. In Computer Science Education, 2009. ICCSE 09. 4th International Conference on, pages 1245 1250, July 2009. [1] Brad Adelberg. NoDoSE - a tool for semi-automatically extracting structured and semistructured data from text documents. SIGMOD Rec., 27(2):283 294, June 1998. [2] Sudhir Agarwal and Michael Genesereth. Extraction and integration of web data by end-users. In Proceedings of the 22Nd ACM International Conference on Conference on Information & Knowledge Management, CIKM 13, pages 2405 2410, New York, NY, USA, 2013. ACM. [3] Chia-Hui Chang and Shao-Chen Lui. Iepad: Information extraction based on pattern discovery. In Proceedings of 2015 Information Processing Society of Japan 165

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