2010 cognitive science informing the design of attention aware social systemsThierry Nabeth
Presented at the Workshop:
“Management and Governance of Online Communities”
27 May 2010, Paris
Organized by the Orange’s Chair "Innovation and regulation in digital services“
of Ecole Polytechnique, and Télécom ParisTech
This was a project with Nokia, building a basis towards life sensing. In particular, accelerometer is not too strong in detecting in-vehicle mode. We used the data-driven approach and teased out a couple of other non-GPS sensors that appear strong for user in-vehicle detection.
Intelligent route planning for sustainable mobilitymichaljakob
This document discusses route planning and summarizes the work of Michal Jakob and colleagues on intelligent route planning algorithms. It provides an overview of journey planning historically and in next-generation systems. It also describes their research on multi-criteria bicycle routing algorithms and metaplanning-based approaches to intermodal trip planning that integrate multiple transport modes and subplanners. The document concludes by discussing further research topics in route planning.
A Context-Aware Retrieval System for Mobile Applicationsmarcopavan83
We present a prototype recommendation system for mobile applications that exploits a rather general description of the user’s context. One of the main features of the proposed so- lution is the proactive and completely automated procedure of querying the apps marketplace, able to retrieve a set of apps and to rank them on the basis of the current situation of the user. We also present a first experimental evaluation that confirms the effectiveness of the general design and im- plementation choices and sheds some light on the peculiar features and critical issues of recommendation systems for mobile applications.
Slides from the presentation of TFMAP at SIGIR 2012.
TFMAP, is a Collaborative Filtering model that directly maximizes Mean Average Precision with the aim of creating an optimally ranked list of items for individual users under a given context. TFMAP uses tensor factorization to model implicit feedback data (e.g., purchases, clicks) along with contextual information
The document discusses massive sensing from both current and future perspectives, including the types of sensors in phones now, the concept of the Internet of Things connecting billions of sensors to share data through the cloud, and the potential for future sensing technologies like embedded sensors and their implications for applications in areas like health, environment, and cities.
2010 cognitive science informing the design of attention aware social systemsThierry Nabeth
Presented at the Workshop:
“Management and Governance of Online Communities”
27 May 2010, Paris
Organized by the Orange’s Chair "Innovation and regulation in digital services“
of Ecole Polytechnique, and Télécom ParisTech
This was a project with Nokia, building a basis towards life sensing. In particular, accelerometer is not too strong in detecting in-vehicle mode. We used the data-driven approach and teased out a couple of other non-GPS sensors that appear strong for user in-vehicle detection.
Intelligent route planning for sustainable mobilitymichaljakob
This document discusses route planning and summarizes the work of Michal Jakob and colleagues on intelligent route planning algorithms. It provides an overview of journey planning historically and in next-generation systems. It also describes their research on multi-criteria bicycle routing algorithms and metaplanning-based approaches to intermodal trip planning that integrate multiple transport modes and subplanners. The document concludes by discussing further research topics in route planning.
A Context-Aware Retrieval System for Mobile Applicationsmarcopavan83
We present a prototype recommendation system for mobile applications that exploits a rather general description of the user’s context. One of the main features of the proposed so- lution is the proactive and completely automated procedure of querying the apps marketplace, able to retrieve a set of apps and to rank them on the basis of the current situation of the user. We also present a first experimental evaluation that confirms the effectiveness of the general design and im- plementation choices and sheds some light on the peculiar features and critical issues of recommendation systems for mobile applications.
Slides from the presentation of TFMAP at SIGIR 2012.
TFMAP, is a Collaborative Filtering model that directly maximizes Mean Average Precision with the aim of creating an optimally ranked list of items for individual users under a given context. TFMAP uses tensor factorization to model implicit feedback data (e.g., purchases, clicks) along with contextual information
The document discusses massive sensing from both current and future perspectives, including the types of sensors in phones now, the concept of the Internet of Things connecting billions of sensors to share data through the cloud, and the potential for future sensing technologies like embedded sensors and their implications for applications in areas like health, environment, and cities.
이웃사촌! 이제는 옛말처럼 느껴집니다.
누구나 한번쯤은 이웃과 주차로 인해 불쾌했던 경험이 있었을 것입니다!
주차를 통해서 이웃과의 관계를 회복하고... 이웃과 친구가 되시길 희망합니다!
1. 처음에는 '공간 공유' 전체를 서비스 범위로 잡았으나 선택과 집중을 했습니다.
2. 공간 가운데 많은 사람들이 Pain Point를 높게 느끼는 공간이 바로 주차장입니다.
3. 또한, 이 공간은 공유를 통해 훼손율이 적고 주창공간에 대한 기대와 실망도 크지 않았습니다.
4. 위치기반 웹(모바일)서비스를 통해 거래관리와 매칭의 신뢰형성 등의 비용절감과 편이성을 보장할수 있습니다.
5. UX실무를 담당자 6명이 모여 사용자의 숨은 니즈를 찾아서 서비스를 만들어 보았습니다!
6. 10분이면 슬라이드를 모두 보실 수 있습니다. 꼭 읽어보시고 많은 의견 부탁드립니다!
2017 스마트창작터 시장검증계획서
음성인식 기반의 지역 캐릭터 시스템
흄 대표 이정헌 작성
음성으로 사용자가 원하는 서비스를 찾아서 실행시켜 준다.
SMS 및 카카오톡으로 인공지능 대답 및 채팅이 가능한 서비스로 확장.
사용자가 질문하는 내용으로부터 사용자 요구사항 통계 및 빅 데이터 도구 제공.
채팅에 제한하지 아니하고, 버스노선, 기차시간, 지역 날씨, 쇼핑몰 옷까지 다양한 분야에서 음성과 채팅으로 서비스를 확장해 나가는데 자연스럽다.
Note (2017-07-12): a more recent version of this slide has been released. https://www.slideshare.net/ByoungHeeKim1/20170629-osia-final
Introduction to deep learning approaches for artificial intelligence (with some practice materials) (mostly in Korean)
(서울대학교 인지과학협동과정, 인지과학방법론 2016년 2학기 강의)
< 2016 3rd UX Trend Report Part1>
라이트브레인 UX 트렌드 리포트 UX Discovery는 해외 다양한 매체들을 통해 하루 평균 50여건의 트렌드를 탐색, 수집, 검토하며 UX적 관점에서 분야별로 분석해서 정리됩니다.
2016 UX Discovery 3호에서는 본격적인 AI시대의 진입을 맞아 선보이는 다양한 AI제품들과 서비스 그리고 빅데이터를 활용한 지진감지 경고앱과 같은 최신앱에서 가상현실, 웨어러블 등 뉴 UX 트랜드들도 한번에 살펴 보실 수 있습니다.
이중 1부에서는 새로운 앱(New App), 인공지능(Artificial Intelligence), 가상현실(Virtual Reality), 증강현실(Augmented Reality) 분야의 최신 트렌드를 담고 있으며
전체 리포트는 총 248페이지로, 나머지 내용 및 자세한 정보는 라이트브레인 웹사이트(www.rightbrain.co.kr)와 블로그에서 확인할 수 있습니다.
The document discusses using geo-semantics and hybrid reasoning for developing smart mobile services, focusing on how combining location data, social networks, and semantics can enable new mobile applications and services. It provides examples of modeling geo-data and ontologies for representing location information and describes how semantic queries can be used to retrieve relevant points-of-interest data. The document also outlines some mobile APIs for accessing semantic geo-data from Android and iPhone applications.
The document discusses geo-social semantics and hybrid reasoning for smart mobile services. It covers topics like linked data networks, representing knowledge in different formats, and an example ontology showing relationships between concepts like employees, companies, and business trips. Tony Lee from Saltlux presents on using semantics and hybrid reasoning to power intelligent location-based applications.
The document discusses human-computer collaboration and the challenges it presents. It notes that computers now have vast computational power and memory but also more complex systems that are difficult for unaided humans to manage. It also mentions that much information is now stored in formats like dynamically combined data rather than human-readable text. Infrastructure is needed to provide background knowledge and put information in a machine-understandable form.
Web Scale Reasoning and the LarKC ProjectSaltlux Inc.
The LarKC project aims to build an integrated pluggable platform for large-scale reasoning. It supports parallelization, distribution, and remote execution. The LarKC platform provides a lightweight core that gives standardized interfaces for combining plug-in components, while the real work is done in the plug-ins. There are three types of LarKC users: those building plug-ins, configuring workflows, and using workflows.
이웃사촌! 이제는 옛말처럼 느껴집니다.
누구나 한번쯤은 이웃과 주차로 인해 불쾌했던 경험이 있었을 것입니다!
주차를 통해서 이웃과의 관계를 회복하고... 이웃과 친구가 되시길 희망합니다!
1. 처음에는 '공간 공유' 전체를 서비스 범위로 잡았으나 선택과 집중을 했습니다.
2. 공간 가운데 많은 사람들이 Pain Point를 높게 느끼는 공간이 바로 주차장입니다.
3. 또한, 이 공간은 공유를 통해 훼손율이 적고 주창공간에 대한 기대와 실망도 크지 않았습니다.
4. 위치기반 웹(모바일)서비스를 통해 거래관리와 매칭의 신뢰형성 등의 비용절감과 편이성을 보장할수 있습니다.
5. UX실무를 담당자 6명이 모여 사용자의 숨은 니즈를 찾아서 서비스를 만들어 보았습니다!
6. 10분이면 슬라이드를 모두 보실 수 있습니다. 꼭 읽어보시고 많은 의견 부탁드립니다!
2017 스마트창작터 시장검증계획서
음성인식 기반의 지역 캐릭터 시스템
흄 대표 이정헌 작성
음성으로 사용자가 원하는 서비스를 찾아서 실행시켜 준다.
SMS 및 카카오톡으로 인공지능 대답 및 채팅이 가능한 서비스로 확장.
사용자가 질문하는 내용으로부터 사용자 요구사항 통계 및 빅 데이터 도구 제공.
채팅에 제한하지 아니하고, 버스노선, 기차시간, 지역 날씨, 쇼핑몰 옷까지 다양한 분야에서 음성과 채팅으로 서비스를 확장해 나가는데 자연스럽다.
Note (2017-07-12): a more recent version of this slide has been released. https://www.slideshare.net/ByoungHeeKim1/20170629-osia-final
Introduction to deep learning approaches for artificial intelligence (with some practice materials) (mostly in Korean)
(서울대학교 인지과학협동과정, 인지과학방법론 2016년 2학기 강의)
< 2016 3rd UX Trend Report Part1>
라이트브레인 UX 트렌드 리포트 UX Discovery는 해외 다양한 매체들을 통해 하루 평균 50여건의 트렌드를 탐색, 수집, 검토하며 UX적 관점에서 분야별로 분석해서 정리됩니다.
2016 UX Discovery 3호에서는 본격적인 AI시대의 진입을 맞아 선보이는 다양한 AI제품들과 서비스 그리고 빅데이터를 활용한 지진감지 경고앱과 같은 최신앱에서 가상현실, 웨어러블 등 뉴 UX 트랜드들도 한번에 살펴 보실 수 있습니다.
이중 1부에서는 새로운 앱(New App), 인공지능(Artificial Intelligence), 가상현실(Virtual Reality), 증강현실(Augmented Reality) 분야의 최신 트렌드를 담고 있으며
전체 리포트는 총 248페이지로, 나머지 내용 및 자세한 정보는 라이트브레인 웹사이트(www.rightbrain.co.kr)와 블로그에서 확인할 수 있습니다.
Similar to Cognitive Planning and Learning for Mobile Platforms (8)
The document discusses using geo-semantics and hybrid reasoning for developing smart mobile services, focusing on how combining location data, social networks, and semantics can enable new mobile applications and services. It provides examples of modeling geo-data and ontologies for representing location information and describes how semantic queries can be used to retrieve relevant points-of-interest data. The document also outlines some mobile APIs for accessing semantic geo-data from Android and iPhone applications.
The document discusses geo-social semantics and hybrid reasoning for smart mobile services. It covers topics like linked data networks, representing knowledge in different formats, and an example ontology showing relationships between concepts like employees, companies, and business trips. Tony Lee from Saltlux presents on using semantics and hybrid reasoning to power intelligent location-based applications.
The document discusses human-computer collaboration and the challenges it presents. It notes that computers now have vast computational power and memory but also more complex systems that are difficult for unaided humans to manage. It also mentions that much information is now stored in formats like dynamically combined data rather than human-readable text. Infrastructure is needed to provide background knowledge and put information in a machine-understandable form.
Web Scale Reasoning and the LarKC ProjectSaltlux Inc.
The LarKC project aims to build an integrated pluggable platform for large-scale reasoning. It supports parallelization, distribution, and remote execution. The LarKC platform provides a lightweight core that gives standardized interfaces for combining plug-in components, while the real work is done in the plug-ins. There are three types of LarKC users: those building plug-ins, configuring workflows, and using workflows.
The Semantic Technology Business: EuropeSaltlux Inc.
This document summarizes the state of semantic technology and artificial intelligence. It notes that while there has been enormous research, companies applying these technologies are just beginning to emerge. Semantic technology is being used increasingly for shallow semantics like tagging on websites and social networks. Deeper uses involving ontologies and rules are still emerging. The document compares the European focus on enabling corporate and public services versus the US consumer focus. It outlines a potential platform for large-scale semantic computing to enable startups and discusses opportunities in both business and consumer applications.
Learning Emergent Knowledge from Blog PostingsSaltlux Inc.
- The document describes a semantic search system that analyzes social web content like blog postings.
- It converts conventional blog postings into "semantic blogs" by adding semantic tags to topics. This allows emerging relationships between bloggers and topics to be discovered.
- The system uses simple semantics from a large number of blog postings and connections between bloggers and topics. This "simple semantic" approach allows new knowledge to emerge from the connections in contrast to traditional ontologies.
Cognitive Planning and Learning for Mobile Platforms
1. 모바일 플랫폼 기반
계획 및 학습 인지 모델 프레임워크계획 및 학습 인지 모델 프레임워크
2 0 1 0 . 7 . 2 6 .
박영택
숭실대학교
2. Agenda
01 Research Goal
02 Scenario
03 Overall System Structure
04 Mobile Task Manager
05 Mobile Activity Aware
06 Mobile Context Log
07 Mobile Social Service
08 Android Environment
3. Mobile Awareness
Local Ad-hoc
Social Service
Activity Log Learning
Social Datamining
Social Learning
Social Dynamics
Activity Log Learning
Incremental Learning
Personal Activity Profile Personalized Reasoning
Automated Planning
Robust Agent
Contextual
Service
Delegation
Personalized
Activity
Learning
3 / 29
4. Research Scopes
상황인지 추론
및 계획 엔진
Ad-hoc 모바일
소셜 서비스
행위인지
기계학습 소셜 서비스기계학습
사용자
행위모니터
모바일
지능프레임워크
Smart
Assistant
4 / 29
8. Application
주요 지능 Modules
Smart Agent
Annoy
Free
Smart
Calendar
Themis
Smart
Call
Social Agent
Social
Recommender
Social
Ad-hoc
Social
Magazine
지능 Infra
Text
Miner
Context
Broker
Scene Text
Analyzer
Social
Engine
RDFS
Inference
Engine
User
Model
Context
Logger
Planning
Engine
8 / 29
9. 주요 지능 Modules
Application
Smart Agent
Annoy
Free
Calendar
Themis Call
Social Agent
Social
Recommender
Social
Ad-hoc
Social
Magazine
Smart Agent
Server
User
Model
지능 Infra
Text
Miner
Context
Broker
Scene Text
Analyzer
Social
Engine
Inference
Engine
User
Model
Context
Logger
Panning
Engine
RDFS IE.
Planning
Engine
Context
Logger
Model
Learner
Context
DB
9 / 29
10. 주요 지능 Modules
Smart Agent
Server
User
Model
SA
RDFS IE
PE
CL
RDFS IE.
Planning
Engine
Context
Logger
Model
Learner
Context
DB
SA
RDFS IE
PE
CL
SA
RDFS IE
PE
CL
SA
RDFS IE
PE
CL
Social Ad-hoc
10 / 29
15. RDFS 추론 엔진 연구 내용Smart Assistance – Calendar with Email
Inbox
Time 2010 JUNE 12 SAT 09:42 AM
From rdfs@gmail.com
Subject 세미나 일정
안녕하세요.
세미나
다음 주 월요일
일 월 화 수 목 금 토
12
13 14 15 16 17 18 19
Calendar
안녕하세요.
모바일인지프레임워크에 대한 세미나가
다음 주 월요일 오후 2시부터 4시까지
601호 회의실에서 있을 예정입니다.
모바일팀원들의 많은 참여 부탁 드립니다.
오후2시부터 4시까지
601호 회의실
모바일팀
13 14 15 16 17 18 19
2010년 6월 14일 (월)
2:00 ~ 4:00 p.m.
601호 회의실
세미나
모바일팀
Text Mining
자연어처리
15 / 29
18. RDFS 추론 엔진 연구 내용Smart Assistance – AnnoyFree
Calendar
2010 JULY 06 Tue
08:30 – 09:00
Daily Meeting at Office
AnnoyFree
Activated
19:00 – 21:00
Dinner with Friends
Daily Meeting at Office
10:00 – 17:00
Workshop at COEX
10:00 – 17:00
Workshop at COEX
Time 09:55
Location 480m from COEX
Time 10:00
Location 150m from COEX
Time 10:15
Location COEX
Bluetooth 5 Colleagues
18 / 29
19. Planning 시나리오
무엇을 도와 드릴까요?
Say it!Speak now...Thinking...
I think you said…
사무실 근처에 있는
근사한 이탈리아 식당에
가고 싶다.
Planning 시나리오
Restaurants
“근처에 괜찮은 한식당”
Movies
“오후에 액션 영화 한편”
Concerts
“요즘 인기 있는 콘서트는”
무엇을 도와 드릴까요?가고 싶다.
Tap text to edit
That’s right!
Go
19 / 29
20. Planning 시나리오
I think you said…
사무실 근처에 있는
근사한 이탈리아 식당에
가고 싶다.
강남구 사무실 근처에 있는
근사한 이탈리아 식당을
찾는 중…
사무실 근처에 있는 근사한
이탈리아 식당에 가고 싶다.
OK! 사무실 근처에 있는
근사한 이탈리아 식당을
다음과 같이 찾았습니다:Restaurants by location, rating
비아디나폴리
강남구 삼성동, 500m Call
Restaurants by location, rating
서울시 강남구 삼성동
154-10 융전빌딩 B1
Planning 시나리오
가고 싶다.
Tap text to edit
That’s right!
Go
찾는 중…다음과 같이 찾았습니다:
비아디나폴리
강남구 삼성동, 500m
La pizza
강남구 논현동, 450m
비엘차퍼스
강남구 신사동, 820m
Call
Call
Call
Restaurants by location, rating
20 / 29
21. 비아디나폴리
강남구 삼성동, 500m Call
Restaurants by location, rating
서울시 강남구 삼성동
154-10 융전빌딩 B1
Speak now...Thinking...
I think you said…
비아디나폴리에
내일 저녁 7시
2명 예약하고 싶다.
Planning 시나리오
Say it!
2명 예약하고 싶다.
Tap text to edit
That’s right!
Go
21 / 29
22. Planning 시나리오
비다디나폴리에 내일 저녁 7시
2명 예약하고 싶다.
잠시만 기다리세요…
비다니나폴리에
내일 저녁 7시 2명 예약가능.
Confirm Reservation
Reservation
Planning 시나리오
Confirm Reservation
Reservation Details
일시 및 시간 내일 7:00 pm
인원 2명
위치 강남구 삼성동
154-10 융전빌딩 B1
수정
이름 장동건
22 / 29
23. Bird’s Eye View
Context
AI Module Interface
Application Application Application. . .
Bird’s Eye View of Proposed System
ServerServer
WebWeb
Mining
SmartPhone Sensor
Context
Broker
Context
Generator
RDFS
Inference
Engine
ML
Interface
Text
Mining
Logger
Planner
Web
Service
Interface
Sensor
WebWeb
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24. Overall Structure
User Model
Activity Aware
Social
Service
Android Task Manager
Mobile
Mobile Task Manager
Local ad-hoc Machine Learning
Activity AwareService
ContextLog
Mobile
RDFS
Inference
Engine
Planner
Text Miner
Context
Server
Sensor, Map, Web, PIMS
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26. Integrated System View
지능형 응용 서비스
3rd Party
Smart
Call
Smart
PIM
Smart
Guider
Smart
Reservation
Social
Caster
Social
Recommender
Social
Finder
Match
Maker
개인화
에이전트 구동
사회화
에이전트 구동
콘텐츠 및
서비스 합성
외부 서비스
연계
사회화
통합 서비스 인터페이스
지능형 서비스 프레임워크
어플리케이션
인공지능 컴포넌트 관리
사회화학습추론 계획
외부
어플리케이션
어댑터
통합 정보 중재
모바일 플랫폼 서비스 구동
Ad-hoc 네트워크 구동
사용자 행위 모니터링
모바일 통합 프레임워크
개방형 모바일 플랫폼 (Android)
단말 하드웨어
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27. Smart Assistant in Android Environment
Intelligent Applications
Android
Application
Android
Service
AI Engines
Android Application Framework
RDFS
Inference
Engine
LearnerPlanner
Social
Engine
Content Provider
Context ProfileRule
Legend
a Service
a Activity
a Content Provider
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28. System Integration
Mobile Artificial Intelligence Framework
.apk Services
RDFS I.E. Planner
Another
Services
AIDL
.jar
Application
Mobile Artificial Intelligence Framework
Server Interface
Context Information
Interface
RDFS
Axiom
Context
Rule
ServerServer
User
Model
Meta
Data
Learned
Activity
Model
28 / 29