1 ontology-based constraint recognition for free-form service requests muhammed al-muhammed david w....

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Ontology-Based Constraint Recognition for Free-Form

Service RequestsMuhammed Al-Muhammed

David W. Embley

Brigham Young University

Supported in part by the National Science Foundation under Grant #0414644.

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A Free-Form Service Request

What’s the weather forecast for Springfield, Illinois, between the 21st and 24th?

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Weather Forecasting ServiceAccess to the National Digital Forecast Database

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Weather Forecasting ServiceAccess to the National Digital Forecast Database

-89.66

39.78

2007-04-21 4

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Request Recognition


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Request Results

53° 34° 10%

54° 39° 14%

50° 37° 41%

55° 40° 70%

MaximumTemp ChanceOfPrecipMinimumTemp


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What Makes this Work?What’s the weather forecast for Springfield, Illinois, between the 21st and 24th?

WeatherReport(x0) is for Latitude(getLatitude(“Illinois”, “Springfield”)) WeatherReport(x0) is for Longitude(getLongitude(“Illinois”, “Springfield”)) WeatherReport(x0) starts on StartDate(NextDate(“21st”)) WeatherReport(x0) is for NumDays(NrDaysBetween(NextDate(“21st”),

NextDate(“24th”))) WeatherReport(x0) has Format(“24 Hourly”) WeatherReport(x0) produces ReportPeriod(x1) ReportPeriod(x1) has MaximumTemperature(x2) ReportPeriod(x1) has MinimumTemperature(x3) ReportPeriod(x1) has PercentChanceOfPrecipitation(x4)

The heart of the problem:constraint recognition

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Ontology-Based Constraint Recognition

City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature

MaximumTemperaturePercentChanceOfPrecipitation

WeatherReport Formathas

is forstarts onis for

is for ->

produces

has has

has

identify

is for

identify

determine

is in

City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in

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City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in

City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in

Add object; satisfy constraints

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City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in

City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in

Formal predicates: object sets & relationship sets

WeatherReport(x) is for Latitude(y)

NumDays(x)

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City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in

City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in

Formal constraints: e.g. functional, mandatory, …

x(WeatherReport(x) 1y(WeatherReport(x) is for Latitude(y))

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City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in

City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in

Data frames: instance recognition; operation recognition

StartDate internal representation: date default value: (today) text representation {monthName}\s+([0]?[1-9] | [12]\d|3[01])(\s*\,)?\s+\d{4} | (the\s+)?([0]?[1-9] | [12]\d|3[01])\s*(th|...)|... toInternalRepresentation(x:string) returns (StartDate) Tomorrow() returns (StartDate) context keywords/phrases: tomorrow|next\s*day | ... NrDaysBetween(x1:StartDate, x2:EndDate) returns (NumDays) context keywords/phrases: between the \s+{x1}\s+and\s+{x2} | ...

NumDays internal representation: integer default value: 1 …

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City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in

City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in


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City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in

City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in


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City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in

City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in


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City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in

City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in

StartDate ... NrDaysBetween(x1:StartDate, x2:EndDate) returns (NumDays) context keywords/phrases: between the \s+{x1}\s+and\s+{x2} | ...


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City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in

City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in


Format … Default value: “24 Hourly” …


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City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in

City

State

EndDate

StartDate

NumDays

Place

Longitude

ZipCode

Latitude

ReportPeriod

MinimumTemperature




is for ->

produces

has has

has

identify

is for

identify

determine

is in


Format … Default value: “24 Hourly” …


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Generated Rel. Calculus QueryWhat’s the weather forecast for Springfield, Illinois between the 21st and 24th?

{ < x2, x3, x4 > | WeatherReport(x0) is for Latitude(getLatitude(“Illinois”, “Springfield”)) WeatherReport(x0) is for Longitude(getLongitude(“Illinois”, “Springfield”)) WeatherReport(x0) starts on StartDate(NextDate(“21st”)) WeatherReport(x0) is for NumDays(NrDaysBetween(NextDate(“21st”),

NextDate(“24th”))) WeatherReport(x0) has Format(“24 Hourly”) WeatherReport(x0) produces ReportPeriod(x1) ReportPeriod(x1) has MaximumTemperature(x2) ReportPeriod(x1) has MinimumTemperature(x3) ReportPeriod(x1) has PercentChanceOfPrecipitation(x4) }

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Experiment Subjects: BYU students Domains:

Doctor/Dentist appointments Car purchase Apartment rental

Requests:

Requests Predicates ArgumentsAppointment 10 126 34Car 15 315 98Apartment 6 107 38Totals 31 548 170

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Results

Recall PrecisionAppointment predicates 0.98 1.00

arguments 0.94 1.00Car predicates 0.99 0.99

arguments 0.98 0.99Apartment predicates 0.97 1.00

arguments 0.92 1.00All predicates 0.98 0.99

arguments 0.95 0.99

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Results





arguments 0.95 0.99

e.g. missed:

“any Monday of this month” “most days of the week”

“a nook” “extra storage”

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Results





arguments 0.95 0.99

e.g. missed:

“I want a Toyota with a cheap price, 2000 would be great …”

The system incorrectly concluded that “2000” was a price.

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Results





arguments 0.95 0.99

Recall: “good” – can improve by improving value recognition

Precision: “excellent” – recognized constraints and valuesalmost cannot be irrelevant

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Implications

Free-form queries: possible Free-form service requests: possible Ontology-based web services

Ontology-based wrapper for web servicesExample: the National Digital Forecast Database

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Wrappers for Web Services

www.deg.byu.edu

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Costs

Manual ontology construction Mitigating observations

Not impossibly hard to build by handData-frame libraryForm-based constructionTable-based semi-automatic construction

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Conclusions

Can process ontology-based free-form requests Experimental recall: can be sufficiently good Experimental precision: nicely bounded within context

Possibilities: Free-form queries Free-form service requests Wrapper for web services

www.deg.byu.edu

1 ontology-based constraint recognition for free-form service requests muhammed al-muhammed david w....

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