Post on 20-May-2015
description
Geo-Social Semantics
and Hybrid Reasoning for
Smart Mobile ServicesSmart Mobile Services
SEMANTICTECHNOLOGY
6 June 2011 / SALTLUX, inc.
Tony LEE / tony@saltlux.com
Linked World
And SemanticsAnd Semantics
Communicating Knowledge 2
Scarecrow : I haven't got a brain... only straw.
Dorothy : How can you talk if you haven't got a brain?
Communicating Knowledge 3
Dorothy : How can you talk if you haven't got a brain?
Scarecrow : I don't know... But some people without brains do an awful lot of talking... don't they?
Dorothy : Yes, I guess you're right
Scarecrow : The sum of the square roots of any two sides of an isosceles triangle is equal to the square root of the remaining side. Oh joy! Rapture! I got a brain! How can I ever thank you enough?
Wizard of Oz: You can't.
Tony’s Brain and Knowledge
Neurons~100B #
~2x # ofWeb Pages
Communicating Knowledge 4
Synapse~100T #
~2# ofWeb Links
650ft (~200m)
650ft
1 : 10001 : 10001 : 10001 : 1000
KnowledgeNetwork
World Wide WebNetwork
InternetNetwork
PeopleNetwork
WordNetNetwork
Musical workNetwork
CommunicationNetwork
Linked DataNetwork
Data, Information and Knowledge
DATA
• symbol, a statement
• facts of the world
INFORMATION
Communicating Knowledge 14
By Gene Bellinger, Durval Castro and Anthony Mills
• collection of data, data in context
• answer about who, what, where, when
KNOWLEDGE
• contextualcontextual organization organization of information
• map of the world inside our brains
• answer about how and why
Knowledge Representations
Natural Language Human language written in letters: “The Earth orbits the sun in an ellipse”
Visual LanguageVisual expression of knowledge in picture, structure diagram, flow chart,and blueprint etc
TaggingKnowledge expressed in keywords, symbols and images related withobjects
Symbolic Language Knowledge expressed in mathematical symbols : x2/a2 + y2/b2 = 1
Decision Tree Tree-shaped graph structure for complex decision making
Combined expression in condition with various rules of human
Human
Communicating Knowledge 15
Rules LanguageCombined expression in condition with various rules of humanknowledge
Database SystemKnowledge expression system composed of objects and relations in atable format
Logical LanguageKnowledge expression of logical symbols and arithmetic operations:Woman ≡ Person ∩ Female
Frame LanguageKnowledge expression of values or pointers for other frames saved inslots
Semantic NetworkKnowledge expression of semantic relation between concepts in a graphstructure
Statistical KnowledgeAllows knowledge expression, machine learning technology combinationbased on probability and statistics
Machine
“Employees working for a company are humans; the company and the employees are legal
entities. The company is able to make a reservation for an employee’s trip. The trip is
available by plane or train that travels in cities within Korea or the U.S.. The companies
and destinations for business trip are located in the cities. Saltlux reserved OZ510 with a
round trip of Seoul and New York for Hong, Kildong.”
Natural Language
Knowledge Representations
Communicating Knowledge 16
Rule Language
(Rule) If someone is flying, he must be on trip.
(Rule) If someone’s trip is reserved in a company, he is an employee of the company.
(+ Rule) For short trip in the same country, an employee should take a train.
(Deduction) Hong kil-dong whose flight is in reservation is an employee of Saltlux.
(Deduction) OZ510 is a flight for the U.S. and Korea.
Legal Entity
Person Company City
Location
Trip
kindOf
kindOf
endsIn
startFrom
books
Legal Entity
Person Company
subclssOf
instanceOf
Person Company
subclssOf
instanceOf
Legal Entity
Name
ID
Gender
Age
Industry
Address
Person Company
subclssOf
instanceOf
Legal Entity
Name (*)
ID (*)
Gender⊆{M,F}
Age > 25
Industry
Addr⊂Seoul
DISJOINT
Ontology
Knowledge Representations
Communicating Knowledge 17
Semantic Network
Employee
Kildong
Saltlux
Airplane TrainKoreanCity
AmericanCity
New york
Seoul
OZ510
kindOf
instnaceOf
instanceOf
instanceOf
instanceOf
participatesIn
instanceOf
Employee
Kildong
Saltlux
subclssOf
instanceOf
instanceOf
Employee
#3502
#4831subclssOf
instanceOf
instanceOf
Position
Kildong
37Manager
P12345
Male
Saltlux
Seoul
C98765
Software
Employee
#3502
#4831
subclssOf
instanceOf
instanceOf
Pos ≠ Exec.
Kildong
37Manager
P12345
Male
Saltlux
Seoul
C98765
Software
(a) Semantic Network (b) (a) + Frame (Slots) (c) (b) + Logical Restrictions
Ontology
Five View Points for Semantic Technology
• URI/RDF based “Web of Data”
• Semantic annotations (RDFa)
• Ontology and Logics • Reasoning, Agent system
Communicating Knowledge 18
• Ontology and Logics
• OWL and RIF
• Reasoning, Agent system
• Personalized services
• Linked semantic data
• Data interoperability
• Semantic Search and Mining
• Recommendation and Discovery
Two Keywords, Today
1. HYBRID
Communicating Knowledge 19
2. MOBILE
Hybrid = Complementary
Communicating Knowledge 20
Strength + Strength
Weakness - Weakness
Hybrid Reasoning : (1) Mixed Method
Logical Reasoning Methods
• Deductive reasoningPremise 1: All humans are mortal. Premise 2: Socrates is a human. Conclusion: Socrates is mortal.
+
Ontology and Rules
Communicating Knowledge 21
Conclusion: Socrates is mortal.
• Inductive reasoningPremise: The sun has risen in the east every morning up until now. Conclusion: The sun will also rise in the east tomorrow.
• Abductive reasoning
• Analogical reasoning
+
Machine Learning
Hybrid Reasoning : (2) Mixed Formalism
+
Communicating Knowledge 22
The relationships among different formalisms(Benjamin Grosof)
Semantic Web Architecture
Hybrid Reasoning : (2) Mixed Formalism
Communicating Knowledge 23
Mobile Communication
Tele - Communication
Geo-Location Sociality
Communicating Knowledge 24
Geo-Semantics
GEO Data, GEO Information and GEO Knowledge
WHAT ISWHAT IS
Communicating Knowledge 26
www.ci.ferndale.wa.us/GIS/GIS.php www.ci.ferndale.wa.us/GIS/GIS.php www.ci.ferndale.wa.us/GIS/GIS.php www.ci.ferndale.wa.us/GIS/GIS.php
WHAT ISWHAT IS
GEOGEO--KNOWLEDGE ?KNOWLEDGE ?
An Evolution of Geo Ontology
Geo Tagging � GPS based POI processing� Connecting location coordinate with the relevant information
Geo Features� Applying classification system by domain� Referring to major geographic classification system
Communicating Knowledge 27
� Referring to major geographic classification systemsuch as GeoNames
Geo Ontology � Building/Applying ontology-based spatial information� Expressing Point/Line/Shape information
Geo Ontology + Rules � Utilizing Geo Ontology and rule-based inference� Applying deduction rules for intelligent spatial information processing
• GeoRSS
• Geo ontology
• Feature ontology
• Feature type ontology
• Spatial relationship ontology
Geospatial Ontologies
Communicating Knowledge 28
• Spatial relationship ontology
• Toponym ontology
• Coordinate reference/spatial
index ontology
• Geodata set/metadata ontology
• Spatial services ontology
• W3C Geospatial Ontology
Core Geographical Concepts: Case Finnish Geo-Ontology
Geo Ontology Examples
Communicating Knowledge 29
by R. Henriksson, 2008
http://www.seco.tkk.fi/publications/2008/henriksson-kauppinen-hyvonen-suo-2008.pdf
• Open data for Geo-
information
• TBL was involved in
• Supporting SPARQL
EndPoint
• Supporting RDF/XML,
Ordnance Survey : OpenData
Communicating Knowledge 30
http://www.ordnancesurvey.co.uk/oswebsite/opendata/http://www.ordnancesurvey.co.uk/oswebsite/opendata/
• Supporting RDF/XML,
Turtle, JSON
• Reference Ontologies- Spatial Relations Ontology- WGS84 Geo Positioning- Gazetteer Ontology- FOAF
Ordnance RDF Gazetteer
Communicating Knowledge 31
http://www.ordnancesurvey.co.uk/oswebsite/partnerships/research/pdf/RDFDescription.pdf
POI and Geo-data modeling by Saltlux
• 28# main category and 600 sub categories for POI classification
• Using SKOS for semantic classification
• Including named places and events
• All data set has its name space, http://www.saltlux.com/geospatial
• Coordination
- http://www.w3.org/2003/01/geo/wgs84_pos#lat
- http://www.w3.org/2003/01/geo/wgs84_pos#long
32
http://www.w3.org/2004/02/skos/core#ConceptScheme http://www.w3.org/2004/02/skos/core#Concept
http://www.saltlux.com/geospatial#Class http://www.saltlux.com/geospatial#Code
http://www.w3.org/2004/02/skos/core#hasTopConcept
http://www.w3.org/2004/02/skos/core#inScheme
http://www.w3.org/2004/02/skos/core#broaderhttp://www.w3.org/2004/02/skos/core#narrower
http://www.w3.org/2004/02/skos/core#broaderTransitivehttp://www.w3.org/2004/02/skos/core#narrowerTransitive
GEO Data ModelSKOS based Taxonomy
Communicating Knowledge
Taxonomy and Property modeling for POI
name
alternate name
description
street-adress
postal-code
categories
url
tel
latitude
longtitude
good for
products and services
specialities
brands
smoking
take-out
transit
wireless
reservations
best nights
alcohol
NO Main Classes
1 Arts & Entertainment
2 Adult Entertainment & Nightlife
3 Sports & Recreation
4 Media & Broadcasting
5 Religious Organizations
6 Transportation
7 Automotive
8 Education & Learning
9 Event Planning & Services
10 Manufacturing & Industry General
Arts & Entertainment Adult Entertainment & Nightlife Sports & Recreation
Arcades Adult Arcades, Casinos Archery
Art Galleries Adult Massage Badminton
Botanical Gardens, Arboretum Adult Novelties & Product Shop Baseball
Cinema Bars & Pubs Basketball
Music Concert Hall Business Clubs Billiards
Open air theatres, Festival Places Audult Comedy Clubs Boating
Theatres Dance Clubs Bowling
Museums Jazz & Blues Clubs Boxing
Astrologers & Psychics Audalt Karaoke Cricket
Social & Interests Clubs Hourse Racing Curling
Talent Agencies & Entertainers Boat Racing Cycling
Party Rentals Bycycle Racing Dance
Ticket Office Car Racing Equestrian
Aquariums Billiard Halls Fencing
Video/DVD, Game Rental Other Adult Entertainments Fishing
Comedy Clubs Fitness Clubs
Circus American Football
Amusement Parks Golf
Zoos Gun/Rifle Ranges
Cartoon Rental Gymnastics
Internet Café Hockey
Karaoke Horse Racing & Equestrian
lottery shop Hunting
Exhibition, show Lacrosse
Folk Village Taekwondo
Sub Classes
…
33
longtitude
device_lat
device_long
hours
fax
payment options
parking
ambiance
amentities
attire
price range
delivery
alcohol
reviews
photo
Year Established
seating
outdoor seating
chef
self service
languages spoken
music
associations
part_of
Communicating Knowledge
11 Financial & Legal Services
12 Health and Medical
13 Beauty and Spas
14 Other Professional Services
15 Travel & Tours
16 Home & Local Services
17 Shopping
18 Government & Public Services
19 Food & Drink
20 Restaurants
21 Other Artifacts
22 Other Natural Objects
23 Utility & Infrastructure
Folk Village Taekwondo
Other Arts Judo
Other Entertainment Kendo
Martial Arts
Motorsports & Racing
Paintball
Parachuting
Racquetball
Rafting/Kayaking
Ringette
Rugby
Running
Scuba
Skateboarding, inline skating
Ice Skating
Skiing
Skydiving
Soccer
Softball
Squash
Surfing
Swimming
Tennis
Track & Field
Volleyball
Wrestling
Aerobic
Yoga
Bungee Jump
Camping
Arenas & Stadiums
Playground
Other Sports
Taxonomy Modeling Property Modeling
Find good restaurants for dating that serves steaks and free parking near by GAGA gallery in Insa-dong.
PREFIX ns: <http://www.saltlux.com/geospatial#>PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> PREFIX dc: <http://purl.org/dc/elements/1.1/>PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> PREFIX xsd: <http://www.w3.org/2001/XMLSchema#> PREFIX wgs: <http://www.w3.org/2003/01/geo/wgs84_pos#>PREFIX f: <http://www.saltlux.com/geo/functions#>SELECT * WHERE {
?res rdf:type ns:NamedPlace;
Semantic queries for geo-data
Communicating Knowledge 34
?res rdf:type ns:NamedPlace;ns:name ?name; wgs:lat ?lat1; wgs:long ?long1;ns:address ?addr1.
OPTIONAL{?res ns:street-address ?straddr1.} ?rel rdf:type ns:NamedPlace;
ns:name ?relname; wgs:lat ?lat2; wgs:long ?long2; ns:address ?addr.
OPTIONAL{?rel ns:street-address ?straddr.} ?rel ns:category ?cate;ns:ambiance ns:ambiance_129;ns:parking ns:parking_9.
?cate rdfs:label ?catename. FILTER (f:distance(?lat1, ?long1, ?lat2, ?long2) <= 300 && ?cate = <http://www.saltlux.com/geospatial#code_655> && ?name = '가가갤러리') } ORDER BY ?relname
Demonstration
Communicating Knowledge 35
MOBILE APIs
• Supporting Mobile APIs by using SPARQL Endpoint
• Working on Android (and iPhone)
function description
findPOIbyAll(java.lang.String name, java.lang.String id, int dist, java.lang.String format)
� 4 argument(name, id, distance, format)
� format: xml, json, id: Category ID
findPOIbyAllCoordinate(java.lang.String id, int dist, double lat, double lon, java.lang.String format)
� 5 argument(id, distance, lat, long, format)
� id: Category ID, format: xml, json
findPOIbyCoordinate(java.lang.String id, int dist, double lat, double lon)
� 4 argument(id, distance, lat, long)
� id: Category ID, format: xml
findPOIbyDist(java.lang.String name, java.lang.String id, int dist) 3 argument(name, id, distance)
Communicating Knowledge 36
findPOIbyDist(java.lang.String name, java.lang.String id, int dist) � 3 argument(name, id, distance)
� name: name of PIO, id: Category ID
findPOIbyName(int dist, java.lang.String name) � 3 argument(distance, name)
� format: xml
findPOIbyFormat(int dist, java.lang.String name, java.lang.String format)
� 3 argument(distance, name, format)
� format: xml, json
findPOIbyID(java.lang.String id) � 1 argument(id)
� id: 특정 상점이 갖는 URI, return: meta data of POI, xml
geoQuery(java.lang.String query, java.lang.String format) � 2 argument(query, format)
� format: xml, json
� query for getting MAP data
query(java.lang.String query, java.lang.String format) � 2 argument(query, format)
� format: xml, json
� SPARQL query
protected void onStart() {
super.onStart();
// Service binding
Intent i = new Intent( this, SparqlEndpoint. class);
boolean ret = bindService(i, mConnection , Context. BIND_AUTO_CREATE);
private ServiceConnection mConnection = new ServiceConnection() {
// Service binding call
public void onServiceConnected(ComponentName name, IBinder servic e) {
// converting from service into ISparqlEndpoint interface
MOBILE APIs
Communicating Knowledge 37
mService = ISparqlEndpoint .Stub. asInterface(service);
mService.query( … );
}
// Closing service
public void onServiceDisconnected(ComponentName name) {
mService = null;
}
};
…
}
[DB]
OpenStreetMap[DB]
DBPedia
[Triple]
LinkedGeoData
(LGD)
Wikipedia
Mapping with
Owl:SameAs,
Jaro distance metric
Name comparing
Triplify
Schema : 24Class
Element : 320mega Nodes,
25mega Ways
Making XML data to Linked Datahttp://www.larkc.eu
Use-case : Urban Computing in LarKC project
Communicating Knowledge 38
Use-case : Urban Computing in LarKC project
Inconsistency check• Some POIs suddenly disappeared at a point and
reappeared at another point which make arrow directions are inconsistent.
Unsuitability check• some of road signs are not properly designed
and installed as specified by the regulation.
Communicating Knowledge 39
Inconsistent road sign Unsuitable road sign
New road sign covers another road sign
Go straight? Or turn right?
and installed as specified by the regulation.
• improperly located road signs such as those not installed within the specified range from junction points are not suitable one.
Continuous planning• Some of POI are destroys and moves or appears
from time to time. One of major POI movement(for example, city hall) may bring many road sign modifications.
[Node Element]
R K E
Node RS KPOI WPOI
[Road Sign & POI Insertion]
R
K
E
sameAs
[Junction & POI Finding]
[Link Element]
startNode endNode
Use-case : Urban Computing in LarKC project
Communicating Knowledge 40
[Way Element]
nextLink
link N
link M
[Road Element]
way N
way M
[Junction & POI Finding]
J1
R1
KE
R2
KE
searching range
J2
K
sameAs
Data Set Comments
Linked Geo Data(LGD)
� 1 billion triples in WGS84 coordinate� Loading LGD full and extracted part of Korea
Open Street Map(OSM)
� Extracting all way information in WGS84 coordinate� Selecting and importing 2 million triples for Seoul
Point Of Interest Data in Korea
(KPOI)
� 1 million POIs related with road signs� Around 4 million triples.
Use-case : Urban Computing in LarKC project
Communicating Knowledge 41
(KPOI)� Around 4 million triples.
Seoul road sign data (RSD)
� Diverse data of Seoul road sign in database� 9515 instance of direction road signs in Seoul� Converting TM coordinate into WGS84 coordinate� Converting RDB into RDF (0.5 million triples)
Korean road signregulations (RSR)
� Around 30 Regulations of road signs� Changing to SparQL for validation check
Mediate Ontology(MO)
� Ontology linking between OSM, KPOI, RSD or other data� Expressivity : subClassOf, subPropertyOf, sameAs, inverseOf
Total : about 1.1 billion triples
Linking, Mapping, Converting, Adjusting
LGD OSM KPOI RSD
Use-case : Urban Computing in LarKC project
Communicating Knowledge 42
Mediate Geo-Ontology
Use-case : Urban Computing in LarKC project
Communicating Knowledge 43
Finding the target POI around 500m from a node of road
PREFIX rsm: <http://www.saltlux.com/rsm#>
PREFIX owl: <http://www.w3.org/2002/07/owl#>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX sgf: <http://www.saltlux.com/geo/functions#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX geo: <http://www.w3.org/2003/01/geo/wgs84_pos#>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
Use-case : Urban Computing in LarKC project
Communicating Knowledge 44
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
select distinct ?targetPOIID
where {
rsm:osmn_436718764 geo:lat ?endNodeLat .
rsm:osmn_436718764 geo:long ?endNodeLong .
rsm:kpoi_12720 geo:lat ?targetNodeLat .
rsm:kpoi_12720 geo:long ?targetNodeLong .
rsm:kpoi_12720 rsm:id ?targetPOIID .
filter ( sgf:distance(?endNodeLat, ?endNodeLong, ?targetNodeLat, ?targetNodeLong) <= 500 )
}
Data: Traffic Flow and Speed Prediction: Data from Milano
� Traffic data from Milano (Italy)
� Data ranging from Mar. 07 to July 09 (849 days)
� 5 min. sampling rate for flow & speed
Milano City Sensor Map
Use-case : Urban Computing in LarKC project
Communicating Knowledge 45
� 5 min. sampling rate for flow & speed
� Traffic flow & speed from
� 209 sensors that are able to classify vehicles, and
� 757 non classifying sensors
� Weather data provided fromhttp://www.ilmeteo.it
� 1 hour sampling rate for weather data
Sensors – Crossroads – Street Categories (multi-colored)
Problem Description: Traffic Flow and Speed Prediction
Traffic Flow [12:00; 12:05] (preprocessed)
Tra
ffic
Flo
w (
# v
ehic
les)
Use-case : Urban Computing in LarKC project
Communicating Knowledge 46
� Predict the traffic flow and speed for the next 24h based on a 5 min. time grid
� Traffic flow and speed forecasts are made on the sensor level for the whole traffic network
� Forecasts: inputs for optimal routing algorithms
Mar. 07 July 09
Mar. 07 July 09
Tra
ffic
Speed (
avera
ge)
Traffic Speed [12:00; 12:05] (preprocessed)
Context Awareness and Geo-Semantics
Communicating Knowledge 47
Source : Flickr.com, David Crow
• physical contexts
: location, time
• environmental contexts
Context Awareness and Geo-Semantics
Communicating Knowledge 48
• environmental contexts
: weather, light, sound levels
• informational contexts
: stock quotes, sports scores
• personal contexts
: health, mood, schedule, activity
• social contexts
: group activity, social relationship
• application contexts
: e-mail, websites visited
• system contexts
: network traffic, status of printers
PersonRelative
Person
personID
hasProfile
health
hasNick
belongTo
Health
disease
bloodType
heartBe
at
bodyTemperature
etcHealthInfo1
preference
interest
Profile
name
age
birth
Nick
nickName
calledBy
Interest
field
detailedField
etcHealthInfo2
job
cellularPhoneNum
Group
groupName
hasMemberuserPriority
privacyLevel
deviceAccessLevel
privacyLevel
height
weight
privacyLevel
privacyLevel
locationInfo
LocationSensor
contact
Contact
privacyLevel
hasSchedule
PolicysubClassOf subClassOf
Session
person
hasTask
Task
taskName
hasSubTask
timeInterval
SubTask
targetProperty
space propertyValue
OperationSubTask
taskPriority
DeviceSubTask
device
timeInstance
delayTime
hasOperation
SearchSubTask
searchWord
delayTime
timeInterval
subClassOfsubClassOf
deviceName
subClassOf
TimeRelation
before
after
during
at
Time
TimeWordMean
timeWord
before
after
at
serviceInterval
date
time
TimeInterval
dateInterval
to
from
timeInterval
subClassOfsubClassOf subClassOf
Space
subClassOfsubClassOf
OfficeSpace
이미지를 표시할 수 없습니다 . 컴퓨터 메모리가 부족하여 이미지를 열 수없거나 이미지가 손상되었습니다 . 컴퓨터를 다시 시작한 후 파일을 다시 여십시오 . 여전히 빨간색 x가나타나면 이미지를 삭제한 다음 다시 삽입해야 합니다 .
HomeSpace
spaceName
Event
timeInterval
actionTask
termsEventTerms
person
operation
deivceName
order
device
EventRelative
space
subClassOfsubClassOf
Space
Device
Person
Ontology for Context Awareness by Saltlux
Communicating Knowledge 49
EtcSensor
sensorID
sensingDataType
sensingTime
coordinate
status
Device
deviceID
remainBattery
coordinate
deviceDefault
owner
Actuator
Display
mode
controlColor
brightness
contras
OperationLevel
operationLevel
Temperature
degree
humidity
Sound
volume
soundType
modeEQ
actuator
Exclusive
device
deviceName
hasSensor
menuDisplayTime
Communication
powerStatus
Light
bright
color
PowerdeviceAccessLevel
LocationSensor
sensorID
sensingTime
coordinate
status
subClassOfsubClassOf
Sensor
sensingDataType
EntityRelative
alternativeDevice
Broadcast
station
channelisWork
Player
track
playerStatus
OpenClose
ocStatus
IPaddress
hasSchedule
registerService
DeviceAccessLevel
level
PrivacyLevel
level
Level
subClassOfsubClassOf
UserPriority
level
TaskPriority
level
subClassOf
Priority
subClassOf
subClassOf subClassOf
who
Schedule
title
to
withWhom
briefingContents
where
from
TaskType
RequestInformation
queryLiteral
deviceName
hasOperationO
DeviceTask
Operation
targetProperty
propertyValue
UserCommand
IPAdd
requestTime
hasServiceTime
hasTaskTypeO
O
TimeRelation
from
deviceID
subClassOf subClassOf
nodeType
moviePlace
personID
macID
to
at
UserCommandRelative
catagory
BatchTask
taskData
taskName
subClassOf
subClassOf
subClassOf
LocationSensor
Device
Person
etcSensor
spaceName
device
locationSensor
etcSensor
owner
Person
Dynamic Context
Inferred Context
Conte
xt
Model
Conte
xt
Rule
s
CONTEXT
DeviceUser
CONTEXT OWNER
QoC
CONTEXT MANAGERSENSOR / NETWORK
Filter
Collector
Concept of Context Driven Mobile Services
Communicating Knowledge 50
Smart Mobile Service
ServicePersonalization
CONTEXT-AWARE SERVICE
ServiceAdaptation
ServiceDiscovery
Context Aware Platform by Saltlux
Communicating Knowledge 51
Life Logging from Smart Phone
Use-case : Life Logging
Communicating Knowledge 52
Use-case : Life Logging
Life Logging as RDF data � Context Aware (Inductions: ML)
Communicating Knowledge 53
Sat Sun Sat Sun Sat Sun Sat Sun Sat Sun
Sickat Home
Use-case : Analysis of Life Pattern
Communicating Knowledge 54
at Home
WorkplaceWorkplaceWorkplaceWorkplace
Bus_BBus_BBus_BBus_B
Bus_ABus_ABus_ABus_A
Use-case : Trajectory Awareness
Hybrid Reasoning : DL Reasoning + Induction(Machine Learning)
Communicating Knowledge 55
HomeHomeHomeHome
Bus_EBus_EBus_EBus_EBus_DBus_DBus_DBus_D
Bus_CBus_CBus_CBus_C
Clustering CalculationSelection
Use-case : Trajectory Awareness
Home Detection
Workplace Detection
Hybrid Reasoning : DL Reasoning + Induction(Machine Learning)
SPARQL Query and DL Reasoning
Communicating Knowledge 56
GPS Log
Data
Clustering CalculationSelection
Cleansing MatchingSegmentation
Bus Stop Detection
SampledSampledSampledSampledMobileLogMobileLogMobileLogMobileLog
DataDataDataData
Main Line ExtractingMain Line ExtractingMain Line ExtractingMain Line Extracting
LineLineLineLineThickeningThickeningThickeningThickening
LineLineLineLineThinningThinningThinningThinning
LineLineLineLineGeneratingGeneratingGeneratingGenerating
Commute Trajectory LearningCommute Trajectory LearningCommute Trajectory LearningCommute Trajectory Learning
TrajectoryTrajectoryTrajectoryTrajectoryTracingTracingTracingTracing
TrajectoryTrajectoryTrajectoryTrajectoryClusteringClusteringClusteringClustering
TrajectoryTrajectoryTrajectoryTrajectoryGraphGraphGraphGraph
Use-case : Trajectory Awareness
Hybrid Reasoning : DL Reasoning + Induction(Machine Learning)
Communicating Knowledge 57
E1 � E3 � E5 � E7
Wed Nov 17 08:06:19 9min
Mon Nov 22 08:06:34 10min
Sat Nov 27 09:28:27 14min
E1�E2� E6 � E7
Thu Nov 18 09:52:35 13 min
Fri Nov 19 09:22:32 10 min
Sat Nov 20 09:44;30 13min
Thu Nov 23 08:18;39 6min
Wed Nov 24 12:35:52 15min
Thu Nov 25 09:31:23 14 min
Fri Nov 26 09:38:21 10 min
E4
V1
V4
E3
E1
E5
E7
V6
E6
E2
V3
V2
V5E4
V1
V4
E3
E1
E5
E7
V6
E6
E2
V3
V2
V5
1. No Accident and Disaster
Use-case : ITS of u-City
2. Finding Accident and Disaster : Recommending Detour Path
Communicating Knowledge 58
3. Finding Accident and Disaster but it could be recovered soon
Use-case : Ontology model for ITS
Communicating Knowledge 59
System Overview
• 4 System blocks
• OS : Windows Server
• Platform : J2EE based POJO
(Pure Object Java Object)
• Supporting Web service
Context Aware System
Triple Store
Rule Store
Query Engine
Reasoner
ServiceInterface
ServiceHandler
Situation ReasoningService Manager
Use-Case : Water and Gas Pipeline Management
Context-Aware Disaster Management POC by Saltlux
Communicating Knowledge 60
• Supporting Web service
ContextAwareSystem
DisasterCenter
DashBoard
ControlCenterWeb
ServiceSensorData
GIS Data
LogsData Layer
Rule StoreReasonerHandler
Context Filter
Context Collector
Instance Population
Instance Manager
Context ManagerContext Acquisition
Context-Aware Disaster Management POC by Saltlux
Use-Case : Water and Gas Pipeline Management
Communicating Knowledge 61
Sensor Monitoring Discover Leakage Area
Infer Leakage Pipe Link Automatic Alert Recom. Detour Path
Leakage Detection
Social Semantics
1. Structural features• Small world : six degree of separation
• Unfair world : governed by power law
• Strength of weak relationship
Characteristics of Social Network and Networking
Communicating Knowledge 63
• Strength of weak relationship
2. Synchronization and Amplification
3. Empowerment in Network
• Six degrees of separation
- Experiment : Six degrees of Kevin Bacon
• Does internet and SNS make it shorter?
Structure : Small World
Communicating Knowledge 64
make it shorter?
- Yes or No ?
- Average degrees in FB : 5.73
- Maximum degree in FB : 12
- Average degrees in TW : 4.67
- Average degrees in WP : 4.5
• Scale-Free Network
- Governed by power law
- Like Pareto and long tail principle
• Evolving to HUB network
- Portal(google), SNS(FB, TW)
Structure : Unfair World
Communicating Knowledge 65
- Portal(google), SNS(FB, TW)
- Airport, logistics(Fedex)
• Unfair world, reality
- men-women network
- The rich get richer and the poor get poorer
99
Structure : Unfair World
Communicating Knowledge 66
66
• Strong and Closed Network
- Mafia organization, trust network
- no secret, no new information
• Weak and Open Network
- a broker among heterogeneous netsVS.
Strength of Weak Relationship
Communicating Knowledge 67
- a broker among heterogeneous nets
- controller of network and info. flow
• Strength of Weakness- multiple and cross discipline become more important
- getting new job and ideas, building new business and innovation
VS.
Synchronization and Amplification
Communicating Knowledge 68
Infection of antismoking , fatness and etc like disease
Synchronization and Amplification : infection
Communicating Knowledge 69
Empowerment and democracy in Social network
Communicating Knowledge 70
Power Law VS. Power Dispersion
• Social Networks : networks based on the relation between people
• Semantic Social Network : RDF representations of social network and data
Foaf:knows
Abstraction stack for semantic SNA
Semantic Social Network Analysis
Communicating Knowledge 7171
[Semantic Social Network Analysis, http://journal.webscience.org/141/2/websci09_submission_43.pdf]
Rich graph representations reduced to simple
untyped graphs in order to apply SNA
Foaf:interest
[Paolillo and Wright 2006]
Social NetworkSemantic Network
Text MiningText Mining SNASNA
Semantic Social Network Analysis
Communicating Knowledge 72
Text Mining(Induction)Text Mining(Induction)
SNA(Deduction)
SNA(Deduction)
Semantic Social Network AnalysisSemantic Social Network Analysis
SemanticNetwork
Task
People
Org.
Service
Event
Place
Semantic Social Network Analysis
Communicating Knowledge 73
Family, Colleagues , Community
InformationHub, Broker
Connecting Experts
73
vk : weighting of relation n : number of relations g : total number of entity
gjk : # of shortest path between j and kgjk(i) : # of path having i between j and k
Dijkstra’s algorithmDijkstra’s algorithm
O( | E | + | V | log | V | )
SAMZZIE : Social Semantic Platform by Saltlux
Knowledge Network Services
Knowledge Discovery Control
KDC
Knowledge Network Analysis
KNA
Integrated API
K-DicManager
Social Network Knowledge Knowledge Circulation
User Type Pattern
Social Network
User Type
Pattern
Web User Interface
Topic Rank
DA DAR KNA
Knowledge Circulation
Knowledge Trend
Contents Search
User & Admin Knowledge
Env.
Knowledge Discovery
Query
DAC Schedule
Communicating Knowledge 74
Data Aggregation
DA
Data Analysis and Reasoning
TREDAR
Meta Base Knowledge Base
Email Abst.
Email Aggr.Document
Aggr.Data
AbstractionKnowledge Population
Query Engine
Social Network Analysis
Knowledge Trend Analysis
Circulation Analysis
Pattern Analysis
K-Dic KDQ AuthorityPolicy
U & AEnv.
EmailContents
NE & Annotation
DA
Web Aggr.
ScheduleTopic Trend
Topic Ranker Engine
SN KT KC UTPTopic Rank
DA Scheduler
DAR Scheduler
KNAScheduler
TMS
FeatureExtraction
Use-case : Social Media Analytics
Communicating Knowledge 75
Use-case : VOC Sensing & Analysis (for KT)
Hybrid Reasoning : Induction(Machine Learning) + Deduction(Horn Logic)
Communicating Knowledge 76
Legacy System
MagicN
IPAS
AAA
SAS
Intra Portal Solution
FIMM MagicN
Intelligent Application Service (AS)
Personalized Personalized Search
Intelligent Intelligent Traveling Guide
Shopping Shopping Recommendation
Social Social Network
Local News Etc.,
Enabler
VME
ICE
PS
Internet Portal, BcN, All-IP N/W
empas
DAUM
CDE
ISMS
SICS
ICDS
O&M
Use-case : Intelligent Telco Platform
Communicating Knowledge 77
BGCF
Node-B(WCDMA)
RNC SGSN
SAS
JUICE
S(L)MSC
S(L)MSC
NAVER
InternetTV
BcN
All-IPNetwork
W-CDMA
PCRF
IMS-ALG
TrGW
HSSAuC
IMS Infra
GGSN
Simulation Server
P/I/S-CSCF
• ISMS: Intelligent Subscriber information Mgnt. Server• ICDS: Intelligent Content Delivery Server• SICS: Subscriber Information Collection Server• O&M: Operation & Management Server
Pay for
Call
Profile
•
Profile
• Name: Jerry
Obama
• Age: 12
• Sex: Woman
Profile
• Sex: Woman
Profile
• Name: Elizabeth
Cox
• Age: 12
• Sex: Woman
Profile
• Name: Jane Bush
• Age: 12
lives in
lives in
attend
attend
attend attend
attend
Major Residential Area
Major Activity Area
Use-case : Mobile Social Network Analysis
Communicating Knowledge 78
Call
CallCall
Call
• Age: 12
• Sex: Woman
Profile
• Sex: Woman
Profile
• Name: Edward
Adams
• Age: 11
• Sex: Woman
Profile
• Sex: Woman
Profile
• Name: Jessica
Bailey
• Age: 13
• Sex: Woman
Profile
• Name: Tom Obama
• Age: 16
• Sex: Man
Profile
•
Profile
• Name: Nancy
Obama
• Age: 42
• Sex: Woman
Call
lives in
Family Friends
User Profiling from Network
Use-case : Personal Profile Analysis
Communicating Knowledge 79
Bimodal
Normalμ1 = 38
σ1 = 4.2
w = 0.83
μ2 = 13
σ2 = 2.4
Φ=
각 나이대별 (SMS/VOICE), (성별),
(나이대) 120 클래스 패턴을 이용한 PI
결과
Ontology Population
Legacy Data
Ontology Mapping from Legacy Data
Use-case : Personal Profile Analysis - Semantics
Communicating Knowledge 8080
50 Classes , 58 Relationships , 15 Properties , 57 Rules
Use-case : Hybrid Reasoning DL + Rules
Communicating Knowledge 81
Use-case : Discovering Social Relationship
Communicating Knowledge 8282
Communicating Knowledge 83
Geo-Social Semantics
O2 Platform : Geo-Social Data Cloud by Saltlux
Communicating Knowledge 85
Semantic Geo-Social Platform
GEO Context Provider
SPARQL/XML, JSON
HTTP Engine
Query Engine Geo Context/Social Context Acquisition
Social Context Provider
Social Content EngineGeo Contextmanager
REST/XML, JSON
O2 Platform : Geo-Social Data Cloud by Saltlux
Communicating Knowledge 86
Geo Context Store(Place, Event, etc)
Acquisition
Wrapper Manager
Geo Context Manager
DataFormatter(RDF/XML)Query
Result Formatter
Query Executor
Wrapper
….
Result Formatter
Social ContextIndexer
Social ContextSearcher
Social Context Manager
manager(Admin Console)
Social Context Index
Weather
Traffic
Event
…. Blog News
Opinion Mining and Sentiment Analysis from Twitter
Communicating Knowledge 87
O2 Platform : Ontology model for twitter
sioc:UserAccountsioc:id(xsd:string)
sioc:creator_of
twd:retweet
sioc:has_creator
twd:followertwd:following
twd:post
twd:TwitterUsertwd:screenName(xsd:string)
twd:discuss
Communicating Knowledge 88
geo:SpatialThing geo:NamedPlace
twd:Tweettwd:messageID(xsd:string)
twd:messageTimeStamp(xsd:string)
twd:talksAbout
twd:reply
twd:talksAboutNeutrally
twd:talksAboutPositively
sioc:Postsioc:content(xsd:string)
twd:discuss
twd:talksAboutNegatively
Live Demo
Communicating Knowledge 89
Live Demo
PREFIX f: <java:ext.>SELECT ?poi1 ?poi2 ?user (f:similarWithProbability(data:Alice, ?user) AS ?p) WHERE {?user bot:posts ?t1 . ?t1 bot:talksAboutPositively ?poi1 . ?poi1 a bot:NamedPlace ;
geo:lat ?lat1 ;geo:long ?long1 ;skos:subject ?category .
data:Alice geo:lat ?givenLat ;geo:long ?givenLong ;
tweets about a given kind of POI of people similar to me that tweeted nearby in the last x minutes;
Hybrid Reasoning and Queries
Communicating Knowledge 90
geo:long ?givenLong ; bot:posts ?t2 .
?t2 bot:talksAboutPositively ?poi2 .?poi2 a bot:NamedPlace ;
geo:lat ?lat2 ;geo:long ?long2 ;skos:subject ?category .
FILTER(?t1!=?t2)FILTER(f:similarWithProbability(data:Alice, ?user)>0.5)FILTER((?lat1-?givenLat)<"0.1"^^xsd:float &&
(?lat1-?givenLat)>"-0.1"^^xsd:float &&(?long1-?givenLong)<"0.1"^^xsd:float &&(?long1-?givenLong)>"-0.1"^^xsd:float )
} ORDER BY DESC(?p)LIMIT 10
AR based Location SearchAR based Location Search Reputation AnalysisReputation Analysis
BOTTARI mobile App by Saltlux
Communicating Knowledge 91
Intro screenIntro screen Social Recommendationand Dynamic Social search
Expert Search andReal-time Q&A
DEMO Movie
Communicating Knowledge 92
Future Use-case : Disaster Management
Communicating Knowledge 93
Source : BBC, ESRI
Future Use-case : Disaster Management
Communicating Knowledge 94
Stream Data
Mobile phone Sensors Satellite/CCD images Sensor Networks
Hybrid Stream Reasoning
Mass
agin
g S
erv
ice
Social Media & Networks
Future Use-case : Disaster Management
Communicating Knowledge 95
Stream Data Collection
Deci
sion S
upport
ing
GIS and Geo-Data
Geo-SpatialData Collection
Hybrid Stream Reasoning
DisasterKnowledge
DisasterProcess
DisasterPolicy
DecisionSupporting
System
DashboardAnd
Controller
Mass
agin
g S
erv
ice
Citizen
Government ,Disaster Center
Intelligent Disaster Management System
Technical Tips
And the Company
Communicating Knowledge 96
And the Company
4 Dimensions of Semantic World
Sca
lability
Communicating Knowledge 97
Performace
Expressivity
DataDynamics
Current State of the Art of Technology
Sca
lability
Telco
UbiComp
Soci
al N
et
Year Performance
2005• 500M triples
Communicating Knowledge 98
Expressivity
EnterpriseSearch
Medical
Soci
al N
et
2005• 500M triples• OWL DLP
2010• 30B triples• OWL DL Horst
Current State of the Art of Technology
Communicating Knowledge 99
Sca
lability
Soci
al N
et Telco
UbiCompYear Performance
• 500M triples
Current State of the Art of Technology
Communicating Knowledge 100
Performance
Soci
al N
et Telco
EnterpriseSearch
Medical
2005• 500M triples• 1~40S (LUBM1000)
2010• 30B triples• 0.01~5S (LUBM1000)
Search
Perf
orm
ance
Telco
UbiComp
Year Performance
2005• 1~50S (LUBM1000)
Current State of the Art of Technology
Communicating Knowledge 101
Expressivity
Soci
al
Net
Medical
2005• 1~50S (LUBM1000)• OWL DLP
2009• 0.01~5S (L1000)• OWL DL Horst
How to move Maginot Lines?
Sca
lability
Sca
lability
?
Communicating Knowledge 102
Expressivity Expressivity
?
6 Solutions
Enhanced algorithm
Materialization
Distributed Computing
CurrentState of the Art
ImprovedResults
Communicating Knowledge 103
Distributed Computing
Approximation
Lean KR model
Query optimization+ Query/Data Cache
Wining Strategies
Algorithm Materialization
Query
Medical
E. Search
Social Net
Mobile
Ubiquitous
Communicating Knowledge 104
Distribution
ApproximationLean KR model
QueryOptimization(+ Cache)
Company Overview
Our Mission is
“Communicating Knowledge” for People.
� Company Name Saltlux, Inc. (Since 1979)
� President & CEO Tony (Kyung-il) Lee
� Headquarter Seoul, Korea Tel) +82 2 3402 0081
Communicating Knowledge 105
� Subsidiaries Japan(Tokyo), China(Chingtao), Vietnam(Hanoi)
� URL www.saltlux.com
� Research Lab HLT Laboratory (Member of EU FP6, FP7 projects)
� Investor JAFCO ASIA
�Main Products [IN2] : Semantic Search Platform
STORM : Semantic Business Platform
OWLIM : Semantic Web Search Service
Knowledge Communication Company
Tech/Biz Consulting Software Solution Innovative Service
Business Items
Communicating Knowledge 106
Web 3.0 &
Semantic Web
Ubiquitous
& MobileSearch 2.0
Text Mining
Semantic Search
Mobile Search
Semantic Web
Semantic Wiki and Blogs
Semantic Annotation
Context Awareness
Personalization
Intelligent Mobile Platform
Semantic Tech.
Good Software(GS) Cert.Asian Top 20 Tech. Comp. Best Software Awards
Trustable Company
International Certifications and Awards“
Communicating Knowledge 107
NationalStandard Product
DISCOVERY
NationalStandard Product
DOR & TMSTechnical
Innovation
INNO-BIZ comp. ISO9001:2000
QualityAssurance DOR &TMS
Digital InnovationAwards
20008HIT products
CustomerSatisfaction
TrasWiz
Best KoreanTech. Cert.
World TopWorld Top--1010 “Semantic Tech. Company” “Semantic Tech. Company” ((ZDnetZDnet))
Gov,, Public28%
Construction3%
Telco27%Law
1%
Manufacture10%
We have provided the unique solutions and services
to over 400 customers during last two years.
Customer Distribution
Communicating Knowledge 108
Finance9%
Univ.,Institute
19%
Enterprise49%
Steel2%
Manufacure11%
1%
Broadcasting5%
Portal13%
Electronics24%
Medical3%
Selected Customers
P A T
Communicating Knowledge 109
Core Technologies of Saltlux
Machine
Learning
Machine
LearningArtificial
Intelligent
Artificial
Intelligent
Natural Language Processing
Natural Language Processing
Text MiningText Mining ReasoningReasoningSemantic
Disambiguation
Semantic
DisambiguationSemantic
Annotation
Semantic
Annotation
Communicating Knowledge 110
Search 2.0
(Semantic Search)
Search 2.0
(Semantic Search)
Semantic Tech.with Ontology
Web 3.0
(Semantic Web)
Web 3.0
(Semantic Web)
Ubiquitous / Mobile
(Context Awareness)
Ubiquitous / Mobile
(Context Awareness)Semantic BPMSemantic BPM
Search & Mining Platform
“[“[IN2]”IN2]”Semantic Business Platform
““STORM”STORM”Semantic Web Search Service
““OWLIM”OWLIM”
Three Products
Saltlux has 3 product brands, [IN2], STORM and OWLIM.
Communicating Knowledge 11134
Semantic Search and Mining Platform [IN2]
[IN2]Discovery 2
Semantic Search Engine
Cloud based[IN2]SSAMZIE
[IN2] Platform
Communicating Knowledge 112
[IN2]DOR
Cloud basedIntegratedSearch Engine
[IN2]SearchBox
ApplianceStyle SearchPortal
[IN2]SSAMZIE
Social Search& Mining Engine
[IN2]HBC
HybridClassification
Engine
112
Semantic Search & Mining : [IN2]Discovery
Communicating Knowledge 113
Knowledge Modeling : SBM5, COMET, OS
Triple storing and management : SOR, AG
Best Semantic Web platform in Asia
STORM : Semantic Business Platform
Communicating Knowledge 114
Semantic Annotation : SEMANO, OPTIMA
Semantic Query & Reasoning : SOR, COMET
Application Modules : SSAMZIE, SemEDIT
37
Characteristics
- Mass & real time semantic metadata
storage and management tool
SOR is integrated framework for semantic metadata searching and
management based on Ontology and reasoning technologies.
STORM : SOR
Communicating Knowledge 115
storage and management tool
- High scalability with distributed comp.
- Automatic data collection and filtering
- Context awareness by connecting
heterogeneous context information
- Including ontology and rule based
reasoning engines
- Ontology instantiation by [IN2]SEMANO
COMET is a collaborative framework allowing multiple clients to collect, store,
retrieve, edit, query and do reasoning, manage versions of stored ontologies.
Key Functions- Ontology Library & CVS
- Ontology Categorizing
- Supporting Ontology Engineering
STORM : COMET
Communicating Knowledge 116
- Supporting Ontology Engineering
- Query Management
- Server Reporting
- User Management
Future Works- Improving multi-user performances
- Web based client
- Improving ACL
- Developing plug-ins for Neon and
Topbraid Composer, etc.
Conclusion
• Open Linked Data
Commons forGeo-Social Semantics
Communicating Knowledge 117
• Open Linked Data
• Open Accessibility
• Open Knowledge Base
Thank
SemanticTechnologybecauseOf
interestedIn
Communicating Knowledge 118
You
BusinessInnovation
interestedIn
willAchieve
contributeTo
Q&A
@@TosajangTosajang
SemanticTechnology