Agenda• Search by keyword only?• All-new search viewpoint!• Search history only?• All-new search application!• Conclusion
Search by Keyword only?• Page search, image search, news search, blog search, feed search etc.• Other choices except “keyword”?• The goal of searches is that find data you want.• They can’t find information you feel positive, e.g. happy, kind, novel, optimistic.
Case study• Financial recession – Unhappy, suffering, pessimistic and negative thinking.• Surfing web – Not only searching! – A lot of netizenes surf web aimlessly every time.
Search by Emotion• Find information make positive emotions for you, like happy, kind, novel, optimistic.• Subjective vs. Objective• Cross-lingual and Cross-region• Happy, Novel, Kind, Excite• Psychology of Emotion – 發現恐懼和快樂都能傳染 . ( 英國醫學期刊 ) – 情緒傳染 , 情緒轉化 .
Strategy• Sample the a lot of news or articles make user happy, optimistic, even think it positively.• Vote or rate them via the all sorts of user, and then raise accuracy and identification.• Extract a large number of positive “key word” and “key phrase” factors through analysis, then group factors into the several emotion types finally.
Framework• Technical Scope – information retrieval & extract – text mining – natural language processing
Search history only?• The accuracy of results restricted by keywords you inquire.• The results at once before periodically• Google Alerts
Case study• Plan your lunar year vacation.• Seek a job you care.• Track the stocks or funds you invest.• Watch the some news headline you concerned in.• Refer to others’ suggestions or opinions.
Personal Agent• The goal-oriented search – Who, What, When, Where and Which.• Search and watch topic you interested in.• Show you reports regularly.• Domain-specific issue/event.• Immediate vs. Regular• Raw data vs. Processed information
Strategy• Each agent is scheduled to do searching, extracting, voting or rating.• Each mission is limited in: – Domain-specific issue/event – Who, What, When, Where and Which.• Build several core comparator, e.g. price, salary...• Extract the summary of articles through analysis, then group summaries into the several sections finally.
Framework• Technical scope – information retrieval & extract – text mining – natural language processing – machine learning – intelligent agent
Distributed computing• Execute the distributed computing supported by all users, like searching, extracting, voting or rating.• One eSobi, one computing agent.• Web servers only act as the coordinator and collector.
Conclusion• eSobi in the world (Ant) vs. servers of Google, Yahoo, Amazon (Elephant)• Patent family• Q&A