1. Meaningful Labeling of Integrated Query Interfaces
Eduard C. Dragut (speaker)
Clement Yu
Weiyi Meng
University of Illinois at Chicago
SUNY at Binghamton
VLDB 2006, Seoul, Korea

2. A Motivating Scenario Looking for a ticket
Chicago – Seoul, September 10th – September 17th
delta.com
orbitz.com
expedia.com
A user looking for the “best” price for a ticket:
Has to explore multiple sources
It is tedious, frustrating and time-consuming
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Meaningful Labeling of Integrated Query Interfaces

3. Unified query interface
The goal
Provide a unified way to query multiple sources in the same domain
The Web
Unified query interface
Airfare.com
priceline.com
Formulate the query
united.com
delta.com
nwa.com
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Meaningful Labeling of Integrated Query Interfaces

4. Overview Integrating Query Interfaces
Auto
Cluster query
interfaces
Peng04
Extract query
interfaces
He05, Zhang04
Various formats
e.g. ASCII files
Car Rental
Match query interfaces
B.He03, Dhamankar04, Doan02, Madhavan05,
Wu04
Books
Airfare
(Deep) Web
Integration
of Interfaces
H.He03,
Dragut 06
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Meaningful Labeling of Integrated Query Interfaces

5. Overview Integrating Query Interfaces
Integration Steps:
Structural merging of query interfaces [He03 et al, Dragut06 et al]
Grouping constraints
Ancestor-Descendant relationships
Determining the domain of each global field in the integrated interface [He03 et al]
Meaningful labeling of the integrated interface
The topic of this presentation
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Meaningful Labeling of Integrated Query Interfaces

6. Motivation of Naming
A query interface needs to be easily understood by any user, irrespective of his/her background
The study of query interfaces in the seven domains used in our experiment revealed that the designers of query interfaces follow some “hidden” norms:
there are certain relationships between the labels of the fields in the same groups
E.g., all plurals
the labels of the (super) groups semantically characterize the set of fields underneath them
The semantic ambiguity problem
Synonyms and homonyms are the two sources of naming conflicts [Batini86 et al, Bright94 et al]
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Meaningful Labeling of Integrated Query Interfaces

7. The objectives
The main goal is to provide a systematic way to label fields in the integrated query interface so that the concepts on the integrated query interface are easily understood by ordinary users.
Validated undergoing a survey
Provide a set of desirable properties required in order to have consistent labels for the attributes within an integrated interface so that users have no difficulty in understanding it.
Not covered in detail
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Meaningful Labeling of Integrated Query Interfaces

8. Naming Algorithm The input
A set of query interfaces in the same domain
E.g. Airline domain: Delta, AA, NWA, Orbitz, Travelocity
Each query interface is represented hierarchically [Wu04]
The mapping between the fields of the query interfaces.
Organized in clusters (e.g. [Wu04 et al, B.He03 et al])
The set of groups of fields given by the merge algorithm [Dragut06 et al]
The integrated query interface given by the merge algorithm as a schema tree [Dragut06 et al]
vacations.net
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Meaningful Labeling of Integrated Query Interfaces

9. An Example of Input
Three fragments of query interfaces represented hierarchically
The mapping between them, i.e. the set of clusters
c_DepCity
c_DestCity
c_DepMonth
c_DepDay
c_DepTime
c_DepYear
(Travel,3)
(Travel,4)
(Travel,7)
(Travel,6)
(Travel,8)
(Travel,null)
(PriceLine,2)
(PriceLine,3)
(PriceLine,5)
(PriceLine,6)
(PriceLine,null)
(PriceLine,7)
(British,2)
(British,3)
(British,9)
(British,8)
(British,null)
c_Aduts
c_Infants
c_Children
c_Seniors
c_Airlines
c_Class
(Travel,14)
(Travel,15)
(Travel,16)
(Travel,12)
(PriceLine,12)
(PriceLine,14)
(PriceLine,13)
(British,5)
(British,6)
(British,13)
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Meaningful Labeling of Integrated Query Interfaces

10. Naming Algorithm - Sketch
Step 1: Consistent labeling of the fields
Fields in the same group - use intersect-and-union strategy
Isolated fields, no consistency required
Root fields - treated as a group
Output: each group of fields (or field) has a set of candidate labels, possibly empty
Step 2: Consistent labeling of the internal nodes
For each internal node, starting from the lowest level to the root, apply a set of inference rules on labels
Output: each internal node has a set of candidate labels, possibly empty
Step 3: Enforce consistency within the entire integrated interface
Not covered
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Meaningful Labeling of Integrated Query Interfaces

11. Preliminaries
Normalization [e.g., He03 et al, Madhavan01 et al , Rahm01 et al]
E.g. Adults (18-64) becomes adult
Semantic relationships among complex labels need to be established
E.g., synonymy, hypernymy/ hyponymy
Main issues
Thesauruses provide semantic relationships only for individual content words (e.g., WordNet [Fellbaum98])
How to show that Area of Study is a synonym of Field of Work in the Job domain?
How to show that Class is a hypernym of Class of Tickets in the Airline domain?
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Meaningful Labeling of Integrated Query Interfaces

12. Preliminaries Manipulation of labels
A label is seen as a set of normalized content words
E.g., {area, study} corresponds to Area of Study
E.g., {field, work} corresponds to Field of Work
Area of Study is a synonym of Field of Work
Area is synonym of Field (by WordNet)
Study is synonym of Work (by WordNet)
Most descriptive vs. most general labels
e.g. Category, Job Category, Area of Work, Function
Category and Function – too general
Job Category and Area of Work – descriptive, avoids confusion
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Meaningful Labeling of Integrated Query Interfaces

13. Consistent Labeling of Groups of Fields
Assumption:
The labels given by a query interface for the fields in the same group are consistent
Organize the labels of a group in a relation-like form, called group relation
General idea to build a consistent solution:
Combine multiple rows of consistent labels until a label is assigned to each field in the group
Cluster/schema
c_Senior
c_Adult
c_Child
c_Infant aa
Adults
Children
airfareplanet
Adult
Child
Infant
Airtravel
British
Seniors
Economytravel
Infants
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Meaningful Labeling of Integrated Query Interfaces

14. Consistent Labeling of Groups of Fields
Levels of Consistency
String Level
Two distinct tuples belong to this level of consistency if they have the same label for a cluster in the group relation
Equality Level
Two distinct tuples belong to this level of consistency if they have equal labels for a cluster in the group relation
Synonymy Level
Two distinct tuples belong to this level of consistency if they have synonym labels for a cluster in the group relation
Cluster/schema
c_NumConnections
c_TicketClass
c_Airline aa
NonStop
Choose an Airline
airfare
Number of Connections
Airline Preference
alldest
Class of Ticket
Preferred Airline
cheap
Max Number of Stops
msn
Class
Airline
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Meaningful Labeling of Integrated Query Interfaces

15. Consistent Labeling of Internal Nodes
The problem
Given an internal node in the integrated interface, determine a label that is semantically suitable for it, i.e. its semantic is rich enough to cover the semantics of all its descendant leaf nodes
An example
a fragment of the integrated interface of real Estate domain
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Meaningful Labeling of Integrated Query Interfaces

16. Consistent Labeling of Internal Nodes
In assigning labels to internal nodes we mainly exploit two types of knowledge:
The semantic relationship among the labels of the internal nodes in the individual schema trees
The relationship between internal nodes of source schema trees with overlapping sets of descendent leaves
The two types of knowledge are employed to derive a set of logical inference rules among the textual labels
Some of them will be exemplified next
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Meaningful Labeling of Integrated Query Interfaces

17. Consistent Labeling of Internal Nodes
First logical inference
Informally, consider two internal nodes v1 and v2 of two distinct source schema trees with the property that:
v1’s set of descendant leaves is a subset of v2’s set of descendant leaves nodes,
and v1’s label is a hypernym of v2’s label
Then the labels of the two nodes are semantically equivalent within the given domain of discourse
An example:
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Meaningful Labeling of Integrated Query Interfaces

18. Consistent Labeling of Internal Nodes
Second logical inference (the idea):
The same label is assigned to internal nodes in multiple source query interfaces and the descendant leaves of each such internal node are among those of the internal node in the integrated interface for which a label is sought.
An example:
Fragment integrated query interface
Within source query interfaces
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Meaningful Labeling of Integrated Query Interfaces

19. Consistent Labeling of Internal Nodes
Third logical inference (hypernymy scenario)
Informally, consider two internal nodes v1 and v2 of two distinct source schema trees with the property that:
v1’s label is a hypernym of v2’s label
Then v1’s label semantically covers the union of the descendant nodes of the two nodes.
An example:
Fragment integrated query interface
Within source query interfaces
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Meaningful Labeling of Integrated Query Interfaces

20. Where can the instances help?
Discard labels as values
The problem is known as schema element name as value [Xu03, Dhamankar04]
Example, in the Book domain labels like Hardcover or Paperback are data instances of fields with labels like Format or Binding
Reconcile most general vs. most descriptive
The idea is to bound the meaning of the most general label to a more descriptive one
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Meaningful Labeling of Integrated Query Interfaces

21. Experiment Setup Seven real world domain:
# interfaces
Avg. # fields per interface
Avg. # internal nodes per interface
Avg. depth of interfaces
Airfare 20
10.7
5.1
3.6
Automobile
1.7
2.4
Book
5.4
1.3
2.3
Job
4.6
1.1
2.1
Real Estate
6.5
2.7
Car Rentals
10.4
2.5
Hotels 30
7.6
Used also in Wu04 et al, Madhavan05 et al, Dragut06 at al
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Meaningful Labeling of Integrated Query Interfaces

22. Human Acceptance Ignoring Inherited Ambiguity
Experiment
Human Acceptance
Questions asked:
Do you have any difficulty in filling in an entry for each field?
If you do, identify the fields you had difficulty filling in.
Are the fields understandable on the source interfaces?
11 Survey respondents reported the following:
Domain
Labeling Quality
Human Acceptance
Human Acceptance Ignoring Inherited Ambiguity
Airfare
53.0%
96.6%
98.3%
Automobile
79.7%
100.0%
Book
83.3%
98.9%
Job
80.0%
Real Estate
79.1%
97.8%
Car Rentals
52.5%
97.9%
98.2%
Hotels
70.1%
95.3%
96.1%
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Meaningful Labeling of Integrated Query Interfaces

23. Example Integrated Interfaces
Airfare domain integrated interface
The source query interface
Four people found the group confusing
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Meaningful Labeling of Integrated Query Interfaces

24. Example Integrated Interfaces
Auto domain integrated interface
No surveyed person has identified any problem for this integrated query interface
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Meaningful Labeling of Integrated Query Interfaces

25. Thank you for your time and patience!
End
Please visit the project web site
Thank you for your time and patience!
E. Dragut et al -
Meaningful Labeling of Integrated Query Interfaces