research on intelligent information systems

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Research on Intelligent Information Systems Himanshu Gupta Michael Kifer Annie Liu C.R. Ramakrishnan I.V. Ramakrishnan Amanda Stent David Warren Anita Wasilewska

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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 Presentation

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Page 1: Research on  Intelligent Information Systems

Research on Intelligent Information Systems

Himanshu GuptaMichael Kifer

Annie LiuC.R. RamakrishnanI.V. Ramakrishnan

Amanda StentDavid Warren

Anita Wasilewska

Page 2: Research on  Intelligent Information Systems

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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

Page 3: Research on  Intelligent Information Systems

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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;

Page 4: Research on  Intelligent Information Systems

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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

Page 5: Research on  Intelligent Information Systems

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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).

Page 6: Research on  Intelligent Information Systems

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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

Page 7: Research on  Intelligent Information Systems

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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

Page 8: Research on  Intelligent Information Systems

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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)

Page 9: Research on  Intelligent Information Systems

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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

Page 10: Research on  Intelligent Information Systems

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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

Page 11: Research on  Intelligent 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

Page 12: Research on  Intelligent Information Systems

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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)

Page 13: Research on  Intelligent Information Systems

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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

Page 14: Research on  Intelligent Information Systems

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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

Page 15: Research on  Intelligent Information Systems

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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

Page 16: Research on  Intelligent Information Systems

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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)

Page 17: Research on  Intelligent Information Systems

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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)

Page 18: Research on  Intelligent Information Systems

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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!