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모바일 지능 소개 조성배. 발표 순서 4 배경 – 모바일 지능 개요 4 관련 기술 –Logging –Analysis –Learning & Inference –System Architecture 4 Applications.

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Presentation on theme: "모바일 지능 소개 조성배. 발표 순서 4 배경 – 모바일 지능 개요 4 관련 기술 –Logging –Analysis –Learning & Inference –System Architecture 4 Applications."— Presentation transcript:

1 모바일 지능 소개 조성배

2 발표 순서 4 배경 – 모바일 지능 개요 4 관련 기술 –Logging –Analysis –Learning & Inference –System Architecture 4 Applications

3 모바일 디바이스 개발 추세

4 모바일 지능 - 개요 GPS Call SMS 사진 Device MP3 마이닝 모델링 해석 추론 학습 특이성 추출 시맨틱 표현 의미 이해 에피소딕 메모리 정보 생성 정보추천 정보검색 정보관리 Context-aware service Query by memory fraction - 로그수집 / 가공 도구 - 랜드마크 추출엔진 - 모바일 모델링 라이브러리 - 모바일 추론학습 엔진 - 모바일 해석엔진 - 대화 인터페이스 - 모바일 검색엔진 - 아바타 생성 / 제어도구 로그 수집

5 모바일 지능 – 핵심 기술

6 BlueTooth 4 Wireless protocol in the 2.40~2.48 GHz 4 Short-range RF network (5~10 meters) Bluetooth Detecting S/W Placed Bluetooth Detecting Device with Wireless Transmission Logging

7 SenseCAM 4 Microsoft Research 4 2000 VGA Images per day 4 Sensor data (Movement, light level, and temperature) 4 Black Box for human body 4 Triggering taking a picture –Light change –Time, sudden movement, person nearby 4 Reduce blurred images Logging

8 ContextPhone 4 Nokia 60 series 4 Open Source Logging

9 Photo Analysis [O’Sullivan 2006] 4 Who, When, Where 4 Bluetooth : Who was nearby 4 GPS 4 Counting & locating subjects –Open Computer Vision Library 4 Suggesting identities Analysis

10 Face Identification [Davis 2006] 4 Exploiting context information with face recognition algorithm 4 11 users over 9 months: 1057 photos (1402 faces) Recall Precision Analysis Contexts

11 PhotoWhere Analysis Web page parsing & Ranking terms

12 SenSay Learning & Inference 1) Sensor-Context Mapping 2) Context-Action Mapping 1) Sensor-Context Mapping (SOM) 2) Context-Action Mapping (BN)

13 MIT Reality Mining Group 4 Behavior modeling & prediction using simple hidden Markov model –Separation of {office}, {home}, {elsewhere} with > 95% accuracy 4 Relationship Inference –Gaussian mixture model : patterns in proximity between users  type of relationships {Workplace colleagues}, {outside friends}, {people within a user’s circle of friends} with > 90% accuracy –Inclusion of communication logs + SVM : more powerful Learning & Inference

14 Mobile Intelligence [Eric Horvitz 2005] 4 Embedded Intelligence –Embed reasoning machinery or compiled policies in small, portable devices that perform local, real-time sensing 4 Streaming Intelligence –Policies, recommendations, and information can be streamed from server-based learning and reasoning systems to portable devices, based on information from the devices and other sources System Architecture

15 Embedded Intelligence Car Navigation BayesPhone AniDiary SenSay System Architecture

16 Streaming Intelligence JamBayes INCA ComicDiary Serendipity System Architecture

17 NOKIA LifeBlog Applications

18 MIT LifeLog Applications

19 Integration of LifeNet to LifeLog Applications

20 Sources of MyLifeBits Applications

21 MyLifeBits Applications

22 Stuff I’ve Seen (MS Research) Applications

23 SKT 1mm Applications 검색 대화 위치기반 지식 검색


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