1. Context-Aware Internet
Sharma Chakravarthy
UT Arlington
July 9, 2008

2. InfoMosaic
We are working on a project termed InfoMosaic -- to integrate information from heterogeneous sources
One of the motivations is to extend the querying capability to internet instead of being satisfied with search
Today, we know how to search sites individually; but cannot do much when it comes to combining data/information from multiple sources (except in limited/customized ways)
The above requires lots of context information -- as we shall see 2

3. Search: Castles near London
Motivation
Find – Castles near London reachable by train in 2-3 hours
- Decision Making Process
- Manually Integrate Results to arrive at a decision
Schedules
Train Schedules
Castle Results
Search: Castles near London 3

4. Motivation
Example – 1 : Find – 3-Bedroom House in Austin, TX within 2 miles of an “exemplary” school and within 5 miles of Y highway and priced under Z dollar
Example – 2 : Find – A list of openings for Software Engineers in Companies having their stock price over ‘X’ dollars listed in Nasdaq
Example – 3 : Find – Prices of CDs or Records of the Grammy award winner for Folk Category
The GOAL is to integrate information from a small number of heterogeneous sources in different domains

5. Challenges
Query Specification/Refinement/feedback – adaptive capability
Query Planning & Optimization
Query Reformulation/matching to sources
Data Extraction
Data, Schema / Ontology Integration
Result ranking
Result presentation/Visualization
Inconsistency Management /confidence
Security & Privacy
Handling hidden web
Source and semantics Discovery
Generalization to arbitrary domains

6. Search and Querying Some work Search Querying Structured data
Unstructured data

7. Query/search specification
To specify the query, “Retrieve castles near London that are reachable by train in less than 2 hours”
Input
{castle, train, London} or
{train, from, London, to, castle} or
{train, castle, location, city, London, duration, 2 hours} or
{castle, reachable, train, from, London, 2 hours, or, less than}
Use context – profiles, semantics of usage, feedback and any other information to infer the above query or close to a meaningful query!
For instance, the above inputs can also mean:

8. Query/search specification
Input
{castle, train, London} or
{train, from, London, to, castle} or
{train, castle, location, city, London, duration, 2 hours} or
{castle, reachable, train, from, London, 2 hours, or, less than}
Retrieve Castles near London that are reachable by Train
Retrieve Hotels near London that are Castles and can be reached by a Train
Retrieve Books whose title contain the words `Castle' or `Train' written by an author whose name is `London'

9. Useful context information
Domain taxonomies
Attribute associations with concepts in the taxonomy
Types of attributes
operators and their classification – spatial, temporal, other, …
Dictionary ranking of the meaning of words
User feedback on the usage of words or combinations
Resolving ambiguities from the user
Various types of source semantics
Automatic or semi-automatic Discovery of this information is a separate (hard) problem.

10. The InfoMosaic Framework
Ranking
XQueries
Data Store
Spatial
Data
Repository
XML Repository
Data
Integration
Ranking
Final
Result-set
Internet
Users
Query Results
Knowledge-base
Dictionary
Operators
Statistics
Query Execution
and
Data Extraction
Domain
Knowledge
Source
Semantics
Metadata
Ontology
I/O Attributes
Schemas
Query ……
Web
Pages
Spatial DB
Feed back
Query
Plan
Query
Refinement
Module
Query Planner
and
Optimizer
User Query/Inte nt
User
Query
XML
Data
Web
Services
Hidden
Web
Data
Query
Interfaces

11. Current Status Working on Query Specification
Query Planning and Execution
Identifying components of the KB
Identifying source semantics
Discovery of some of the above either automatically or semi-automatically

12. Thank you!