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1 DEIM Forum 2019 B ( ) F word2vec, An Interface for Browsing Topics of Know-How Sites Shuto KAWABATA, Ohkawa YOUHEI,WenbinNIU,ChenZHAO, Takehito UTSURO,and Yasuhide KAWADA Grad. Sch. of Systems and Information Engineering, University of Tsukuba, Tsukuba Japan Faculty of Engineering, Information and Systems, University of Tsukuba, Tsukuba Japan Logworks Co., Ltd. Tokyo , Japan 1. Yahoo! OKWAVE [8] ( ) [9] SVM (Support Vector Machine) [9] 2.

2 D(z n) { } D(z n)= d D z n = argmax P (z u d) z u (u=1,...,k) 1 ( ) ( 1) 4 Google 100 () 10 1,000 AND AND Google Custom Search API (LDA; Latent Dirichlet Allocation) [1] LDA w K LDA z n(n =1,...,K) w P (w z n)(w V ),, d z n P (z n d) (n =1,...,K) d z n P (z n d) (n =1,...,K) P (z n d) d z n 1 AND d S(d) (d D(z n)) z n S(z n) z n D(z n) d ( D(z n)) S(z n) S(z n)= d D(z n) S(d) z n S(z n) s ( S(z n)) s d ( D(z n)) D(s, z n) z n f(s, z n) { } D(s, z n)= d D(z n) s S(d) f(s, z n)= D(s, z n) z n f(s, z n) [2] Wikipedia word2vec [7] 2 3 d S(d) z n f(s, z n) s(d) d s(d) = argmax f(s, z n) s S(d) ( z n = argmax P (z u d)) z u (u=1,...,k) d d s(d) s(d ) sim(v(d),v(d )) = v(s(d)) v(s(d )) v(s(d)) v(s(d )) d d

3 2 ( ) , , , , θ lbd { D i(z n)= d D(z n) d D i(z n), } sim(v(d),v(d )) > = θ lbd z n D(z n) ( 4 ) [2] 4. [5] [5] 30 ( 3) 4 θ lbd [5] dm x z i z j (i = j) d d URL u(d) u(d ) dm(u(d)) dm(u(d )) dm x ( ) i, j, i = j, d D(z i), d D(z j) dm(u(d)) = dm(u(d )) = dm x dm x 6 i) ii) iii) iv) 5 S 2 A B C R 6 u(d) = u(d )= dm(u(d)) = dm(u(d )) =

4 仮説 複数トピックにまたがって出現するドメイン ノウハウサイトのドメインとみなす 図 3 ノウハウサイト候補の選定 ノウハウ記事へのリンク 図 4 ノウハウサイト例 (クエリ フォーカス 就活 の例) 履歴書 Do ( のノウハウの一覧が参照できる可能性が低いと仮定し 複数の トピックにまたがるドメインが上記 i) iv) のいずれかに該当 する場合には そのドメインを除外する そして 以上の一連 の条件を満たすドメインの集合をノウハウサイト候補の集合 S とする クエリ フォーカス 就活 および 結婚 における参照用 ノウハウサイトの例を 図 4 および 図 5 にそれぞれ示す 5. ノウハウサイト候補群閲覧インタフェース 5. 1 概 要 前節の手順によって選定されたノウハウサイト候補群を閲覧 するためのインタフェースを作成する. インタフェースの画面 例を図 6 に示す トップページでは 各ノウハウサイト候補におこえるノウハ ウの話題の分布を俯瞰するため 各サイトにおけるトピックの 有無を表形式で表示する (図 6 におけるマス目の色の有無が 各トピックにおけるウェブページの有無を示す) 各ドメイン

5 ノウハウ記事へのリンク 図 5 ノウハウサイト例 (クエリ フォーカス 結婚 の例) 結婚レシピ ( (ノウハウサイト候補群) ④ 図 6 ノウハウサイト候補群閲覧インタフェース(クエリ フォーカス 就活 の例) dmx のウェブページ集合を D(dmx ) とすると 各ドメインに 含まれるトピックの集合 Z(dmx ) は次式で定義される Z(dmx ) = zn d D(dmx ), zn = argmax zu (u=1,...,k) P (zu d) 本インタフェースでは 文献 [9] において SVM(Support Vec-

6 2 A B C D E tor Machine) SVM ( 1) ( 2) ( 3) ( 4) 6 Do ( 1) 8 ( 2) 6. S 7 Google Custom Search API 8 3 SVM r θ Sr θ ( S) R Sr θ R () 7 7 S 81 R 50 SVM R 7 ( ) [1] API

7 3 ( ) Jobweb Jobrass Do , , , , d P (z n d) z n P (z n d) ( 0.3 ) [6,10] URL K ,640 1,731 1, ,189 1,272 1, ,733 1, t ( 1%) 1 ( 1%) [3] [8] [3] Yahoo LDA

8 [4] [3,8,9] [4] (a) (b) (c) (d) 1 8 [9] [1] D. M. Blei, A. Y. Ng, and M. I. Jordan. Latent Dirichlet allocation. Journal of Machine Learning Research, Vol.3, pp , [2],,,,.. 10 DEIM, [3],,,,,.. 8 DEIM, [4],,,.. 32, [5],,,,,,.. 9 DEIM, [6],,,,.. 33, [7] T. Mikolov, I. Sutskever, K. Chen, G. Corrado, and J. Dean. Distributed representations of words and phrases and their compositionality. In Proc. 26th NIPS, pp , [8],,,,,,.. 7 DEIM, [9] Y. Ohkawa, S. Kawabata, C. Zhao, W. Niu, Y. Lin, T. Utsuro, and Y. Kawada. Identifying tips Web sites of a specific query based on search engine suggests and the topic distribution. In Proc. 3rd ABCSS, pp , [10],,,,,,.. 25, 2019.

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