情報探索／発見 Information Search/Finding/Discovery

1. 情報探索／発見Information Search/Finding/Discovery 長尾真監修，大学生と「情報の活用」－情報探索入門，京都大学図書館情報学研究会発行，１９９９． 研究紹介： SASS他：キーワード推薦

2. 検索 vs. 探索Retrieval vs. Search • Retrieval get back; regain. By The American Heritageｮ Dictionary • Search look over carefully in order to find something = Finding

3. Search Engine • Searching on Internet/Network Is search engine enough for our purposes? • Full text search • Just a beginning for information search/finding • Needs solution-oriented supporting facilities • Difficulties in finding appropriate keywords →SASS

4. SASS(Searching Assistant with Social Selection) • Keyword Recommendation • Choosing keywords that were used by the searchers • Also useful for searcher’s behavior analysis

5. Info. Provider Matchmaking Problem Arrangement so that the information user and the information provider meet each other. →Search Engine: content-oriented Requirement ？ Providing Info. User

6. Interests Information Gathering Intention Formation： Deciding interests Information Collection： Collecting relating information Were is my information? I got what’s important！ Searching useful information Information Collection Clarifying the problem Intention Formation This is it! Referencing Information What should I do? What’s important? Choosing the information Problem

7. Info. User Problems: ①inInformation Collection： Where is the information(documents) I am looking for? ← Supported well: for example by search engines ②in Intention Formation： Difficulty in expressing/clarifying the user’s own intention/need ② ① Idea Collection Info. Provider

8. Clarifying Interests Clarifying Interests Collaboration Information Collection Information Collection Sharing each other’s idea creation Collaborative Support for Idea Creation Referring and using other user’s ideas in your idea creation

9. Search Key KW Recom. Search Engine Idea Creation Info. Collection User Documents Supporting Idea Making with Keyword Recommendation

10. ●Keyword Recommendation so far: Recommending Keywords based on the Information Provider’s Intention ↓ Recommended Keywords: Chosen among the words that Occur in many common documents as input keyword

11. Problems in KW Recommendation from the Information Provider’s Side • Relation based on the co-occurrence is different from the one that will help the users in creating ideas for information finding • Information providers can put popularly used but unrelated keywords in their documents with the intention that their documents are searched as many times as possible.

12. ●Our Approach to Keyword Recommendation Choosing keywords among those used by other users ↓ Analyzing the records of the users’ search log-data and get the keywords for recommendation. Points： ･The keywords used in searching documents reflect the searcher’s(user’s) intention. ･Searching log is useful to find the relationship between the users and the keywords．

13. 検索ログを利用したキーワード推薦システム SASS(Searching Assistant with Social Selection) Features： ① Multiple-View Keyword Recommendation： ー Able to select the viewpoints for recommendation． ② Use of Data Automatically Generates New Data： ーAvoids “Free-Riding” Problem． ③ Applicable to User/Users Group Recommendation： ーCollaborative Filtering． ※Applied to an Information Retrieval System of Fujitsu.

14. SASS Screen Conditions Records Results

15. Group User Search Formula Keyword ●Multiple View Similar Group Group Similar User User Common KW Search Formula Related KW Keyword

16. Summary SASS (Searching Assistant with Social Selection) • Keyword Recommendation based on the Record of the Users Ex-Searches． • Avoidable of Information Providers’ Tricks． • Multi-View Recommendation． User Recommendation, Searching Behavior Analysis． Possibility of Tools for Personnel Division.

17. Future Directions • Keyword Recommendation • Similarity Measure • Visualization • Collaboration with Search Engine • Analysis Tool of Searching Behavior • Searcher Profiling． • Human Resource Management (Skill DB) for Corporate KnowledgeManagement．

18. Towards More Advanced Information Services • Assisting Information Retrieval/Search Keyword Recommendation • Combining with Thesaurus • Thesaurus • 1.A book of synonyms, often including related and contrasting words and antonyms. • 2.A book of selected words or concepts, such as a specialized vocabulary of a particular field, as of medicine or music. • 1分類語彙（ごい）辞典,シソーラス. • 2　知識の宝庫,辞典,百科事典. • 4〔コンピュータ〕シソーラス,類語辞書.

19. アルコール飲料 UF　酒類 NT　混成酒 みりん リキュール 醸造酒 果実酒 ・ぶどう酒 ・りんご酒 BT　飲料 食品 発酵食品 JICST科学技術用語シソーラス “酒類” →“アルコール飲料” “酒類” Too Many Candidates 　→”混成酒“，”醸造酒“， 　“蒸留酒”，“発泡酒” Too Few Candidates 　→”飲料“，”発酵食品“ Keywords Recommendation Combination with Thesaurus UF: used for NT: narrower term BT: broader term

20. KW推薦に関する他の研究 • Kawano: Overview of Mondou web search engine using text mining and information visualizing technologies, ICDL-Kyoto, 2000. • Takano et al.: Associative Information Access Using DualNAVI, ibid. • Kim: Developing a Domain-Specific Document Retrieval Mechanism, PKAW2000.

21. G4:ネットワーク情報サービスAdvanced Network Services • G3で出されたアイディアの中から１つ案を選び，それを実現させる方法の提案を行う Choose one idea among those presented in the G3 or the ones inspired from them. • 実現するために考えるべきテーマの列挙 List the topics to be considered. • それぞれのテーマに関する課題の列挙とその解決策 List the issues to be solved relating to each of the topics. Find out how to solve the issues. • 重要な事：(What’s important?) 案の完成度を上げる Think out the issues and make them practical as possible. • 内容の具体化(Give shape to your ideas.) • 様々な観点からの実現可能性の検討(Consider all things to be practical.) • 他のサービスとの差別化(What are the advantages that differentiate your plan?)