research on intelligent information systems
DESCRIPTION
Himanshu Gupta Michael Kifer Annie Liu C.R. Ramakrishnan I.V. Ramakrishnan Amanda Stent David Warren Anita Wasilewska. Research on Intelligent Information Systems. Intelligent Systems. Relations, Relations, Relations - PowerPoint PPT PresentationTRANSCRIPT
Research on Intelligent Information Systems
Himanshu GuptaMichael Kifer
Annie LiuC.R. RamakrishnanI.V. Ramakrishnan
Amanda StentDavid Warren
Anita Wasilewska
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Computer Science Department
Intelligent Systems Relations, Relations, Relations
Program analysis: “The value of variable x at line 15 depends on the value of variable y”
Workflow systems: “Task 2 can start only after task 1 has started”
Knowledge-base systems: “A and B are at the same level in an organization if their bosses are at the same level”:
C hasSameLevelAs D and C isBossOf A and D isBossOf B then A hasSameLevelAs B
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Computer Science Department
Program Analysis using Relations
“May Point-To” analysis for C programs
[Anderson’95]
p = &q; qp
points_to(P,Q) :- stmt(v(P),addr(Q)).
stmt(v(p),addr(q)). points_to(p,q)
p = &q;
p = q;
p = *q;
*p = q;
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Computer Science Department
“May-Point-To” Analysis - II
p = q; qr1
r2
p
points_to(P,R) :- stmt(v(P),v(Q)), points_to(Q,R).
points_to(P,S) :- stmt(v(P),star(Q)),
points_to(Q,R), points_to(R,S).
p = *q; r1
r2
q
s1
s2
s3
p
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Computer Science Department
“May-Point-To” Analysis - III
*p = q;p
s1
s2
qr1
r2
points_to(R,S) :- stmt(star(P),v(Q)), points_to(P,R),
points_to(Q,S).
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Computer Science Department
Intelligent Systems Deductive Systems
“Given rules that define relationships, find the consequences of these rules”
Data, Knowledge and Workflow Management Systems
Inductive Systems Given emperical observations, find the rules
that model the observation Data mining, machine learning
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Computer Science Department
Research Areas Data, Knowledge and Workflow Management Systems Logic Programming Web Technologies
Semantic Web Agents
Computational Linguistics Machine Learning Data Mining Rule-based deployment and management of ad-hoc
sensor networks
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Computer Science Department
Himanshu Gupta Broad Research Areas: Wireless Networks, Sensor
Networks, Databases. A sensor network is a very large ad hoc wireless
network of resource constrained nodes. Sensor network can be looked upon as a distributed database.
IIS Research Focus: Query processing and optimization in sensor networks Efficient data storage and access in sensor/ad hoc networks Activity representation and recognization in sensor networks
Relevant Courses Taught: CSE 595 (Topics in Sensor Networks; Spring) CSE 532 (Theory of Database Systems) CSE 658 (Seminar in Wireless Networks)
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Computer Science Department
Michael Kifer
Research in Semantic Web Declarative languages for data and
knowledge manipulation F-logic Transaction logic
Integration of Object-Oriented and Deductive paradigms
Flora-2 system Query Optimization Logic Programming & Artificial Intelligence
10
Computer Science Department
Annie Liu Query languages and policy languages:
for querying and updating complex objects and graphs
using rules, object abstraction, and reg exp patterns
Implementation and optimization methods: generating efficient programs from queries answering queries with time and space
guarantees Frameworks and applications:
security policy frameworks and efficient implementations
frameworks for building Web information systems
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Computer Science Department
C. R. Ramakrishnan
Research in logic programming and deductive systems
Logic program evaluation: data structures and algorithms for
Incremental evaluation of programs Constraint processing
Applications Verification of concurrent systems Program analysis Computer system security
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Computer Science Department
I. V. Ramakrishnan
Research in machine learning and web agents
Agents for extracting information from web sources
Extraction from semi-structured sources Classification using machine learning
Applications Personal Information Assistants Web navigation tools for visually impaired Information presentation in constrained
environments (PDAs, cell phones)
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Computer Science Department
Amanda Stent
Computational Linguistics Multimodal and spoken dialog systems
Dialog system engineering Adaptation in dialog
Natural language processing Generation of sentences for text, dialog
Computational theories of discourse Multimedia information extraction
For task learning For multimodal generation
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Computer Science Department
David S. WarrenResearch in Logic Programming and Knowledge
Systems Implementation of Logic Programming
The XSB Tabled Logic Programming System LP Compiler Optimizations Multithreaded Implementations
Tabling in Logic Programming Extensions to include constraints Methodology for using tabled evaluation Efficient evaluation of negation in LP
Applications Deductive Spreadsheets Ontology Management Classification of and Extraction from text descriptions
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Computer Science Department
Anita Wasilewska
Research in Data Mining Syntax and Semantics of Classification Data Mining as Generalization Process; a
Unified Model for Data Mining Methodology for data Mining Projects
Development
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Computer Science Department
A Sampler of Research Projects
Query optimization in deductive systems (Gupta, Liu, C.R. & I.V. Ramakrishnan, Warren)
Voice XML: Adding sound to the web (Kifer, I.V. Ramakrishnan, Stent)
Query-based deployment and management of ad-hoc sensor networks (Gupta)
Dialog-based systems (Stent) Data mining for bio-informatics
(Kifer, I.V. Ramakrishnan, Wasilewska)
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Computer Science Department
A Sampler of Research Projects
Semantic Search Engines (Kifer, I.V. Ramakrishnan)
Program analysis and verification using deductive systems (Liu, C. R. Ramakrishnan)
Ontology mining and management (Kifer, I.V. Ramakrishnan, Warren)
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Computer Science Department
Graduate Courses We Teach
CSE505 -- Computing with Logic CSE507 -- Intro. to Computational Linguistics CSE526 -- Programming Languages CSE532 -- Database systems CSE537 -- Artificial Intelligence CSE541 -- Logic in Computer Science CSE542 -- Speech Processing CSE632 -- Advanced Database Systems CSE641 -- Advanced Logic in Computer Science CSE644 -- Data Mining Concepts and Techniques And watch for our seminars!