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潜在的ディレクレ配分法(LDA)を用いた、経済アナリストの有用度レイティング
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analists_rating_by_lda_hackday_201702
1.
2017年2⽉5⽇ 1 {“id”: 5, “name”:
“少年閣下のインターナショナル”} 潜在的ディリクレ配分法を⽤いた、 経済アナリストの有⽤度レイティング
2.
検索エンジンに変わる何か • 情報⾃体には依存しない • “情報発信元の信頼度”を評価する 情報発信者レイティングエンジン 1.
作ったもの 2
3.
2. 経済アナリストレイティングエンジン 3 WebコンテンツレイティングAI DB Web View クローラ
4.
2. 経済アナリストレイティングエンジン 4 WebコンテンツレイティングAI DB Web View クローラ
5.
3. クローラとAIによるレイティング 5 1. アナリストのコラムとニュースを取得 2.
LDAで、全記事をトピックをつける 3. ニュース記事のトピックについて、事前 に⾔及していたアナリストをより評価す る独⾃のアルゴリズムでレートを計算
6.
4. モデルとデータ 6 1. 潜在的ディレクレ配分法(LDA) 2.
使⽤したデータ - 経済系のニュース・コラム 4年分 - 対象のアナリスト 400⼈ D: ⽂章数 N: ⽂章に含まれる単語数 W: 単語 z: トピック K: トピック数
7.
5. DEMO 7 http://pti.uropan.net/
8.
6. 感想 8 • JP(Japanese
Processing)しんどい • Python + MySQLでUTF-8扱うの無理 • アルゴリズムの実装より、クローラ作った りデータクレンジングのがキツい • ⼈⼯知能(AI)云々より、データのが⼤事
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