searching web services xin (luna) dong, alon halevy, dinh lam, jayant madhavan, ema nemes, jun zhang...
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Searching Web ServicesSearching Web Services
Xin (Luna) DongXin (Luna) Dong, Alon Halevy, Dinh Lam,, Alon Halevy, Dinh Lam,Jayant Madhavan, Ema Nemes, Jun ZhangJayant Madhavan, Ema Nemes, Jun Zhang
University of WashingtonUniversity of Washington
Web Service SearchWeb Service Search Web services are getting popular within Web services are getting popular within
organizations and on the weborganizations and on the web The growing number of web services raises the The growing number of web services raises the
problem of web-service search.problem of web-service search. First-generation web-service search engines do First-generation web-service search engines do
keyword search on web-service descriptionskeyword search on web-service descriptions BindingPoint, Grand Central, Web Service List, BindingPoint, Grand Central, Web Service List,
Salcentral, Web Service of the Day, Remote Methods, Salcentral, Web Service of the Day, Remote Methods, etc.etc.
I. NOT Accurately Specify I. NOT Accurately Specify Users’ Information NeedsUsers’ Information Needs
Nine-day forecast for a city
II. NOT Return Objects II. NOT Return Objects at the Right Levelat the Right Level
There are 31 web services
III. NOT Capture III. NOT Capture the Underlying Semanticsthe Underlying Semantics
Italian CAP
Location Information
LocationInformation
Get Weather Forecast
IV. Users Need to Drill Down to IV. Users Need to Drill Down to Find the Desired OperationsFind the Desired Operations
Choose an operation
IV. Users Need to Drill Down to IV. Users Need to Drill Down to Find the Desired OperationsFind the Desired Operations
GetIraqWeatherInfo
city
Invoke
Enter the input parameters
IV. Users Need to Drill Down to IV. Users Need to Drill Down to Find the Desired OperationsFind the Desired Operations
Results – output
I. Allow Users to AccuratelyI. Allow Users to AccuratelySpecify their NeedsSpecify their Needs
Input: city stateOutput: forecastDescription: the weather in the
next nine days
Template Searchon Operations
II. Return Operations Rather than II. Return Operations Rather than Web ServicesWeb Services
There are 15 operations from 3 web services
III. Capture the Underlying III. Capture the Underlying Structure and SemanticsStructure and Semantics
GetWeatherByCityState(0.48858497)
GetIraqExtendedWeatherInfo(0.47451577)
GetIraqWeatherInfo(0.46325448)
GetNineDayForecastInfo(0.4384773)
IV. Search for Similar OperationsIV. Search for Similar Operations
Returns nine day forecast information for a valid given U.S. zipcode
IV. Search for Similar OperationsIV. Search for Similar Operations
Similar Operations, Inputs, Outputs
Composable with Input, Output
IV. Search for Similar OperationsIV. Search for Similar Operations
Operations that compose with input
getZipInfoByAddress
CityToZip
Jump from operation to operation
V. Composition SearchV. Composition Search
getZipInfoByAddress+GetNineDayForecastInf
o
ShortZipCode+GetNineDayForecastInf
o
Principle I. Principle I. Exploit StructureExploit Structure
Web ServiceCorpus
Web service description
Operation name and description
Input parameter names
Output parameter names
OperationRelevance
Parameter Names Are Highly VariedParameter Names Are Highly Varied Op1: GetTemperatureOp1: GetTemperature
Input: Zip, AuthorizationInput: Zip, Authorization Output: ReturnOutput: Return
Op2: WeatherFetcherOp2: WeatherFetcher Input: PostCodeInput: PostCode Output: TemperatureF, WindChill, HumidityOutput: TemperatureF, WindChill, Humidity
Op3: LocalTimeByZipcodeOp3: LocalTimeByZipcode Input: ZipcodeInput: Zipcode Output: LocalTimeByZipCodeResultOutput: LocalTimeByZipCodeResult
Op4: ZipCodeToCityStateOp4: ZipCodeToCityState Input: ZipCodeInput: ZipCode Output: City, StateOutput: City, State
Op5: CityStateToZipCodeOp5: CityStateToZipCode Input: City, StateInput: City, State Output: ZipCodeOutput: ZipCode
Input parameter names
Output parameter names
PrinciplePrinciple 2: 2: Cluster Parameters into ConceptsCluster Parameters into Concepts
Web ServiceCorpus
Web service description
Operation name and description
Input parameter names & concepts
Output parameter names & concepts
OperationSimilarity
Concepts
Hard questions:Hard questions:What is the distance between my What is the distance between my
home (98036) and the university home (98036) and the university (98195)?(98195)?
What is the weather in Seattle?What is the weather in Seattle?
Ask Google?Ask Google?
Distance between 98036 and 98195
FOREST RESOURCE IMPROVEMENT ASSOCIATION OF ALBERTA
Web-Service Automatic InvocationWeb-Service Automatic Invocation
<GetDistance>14.27101
<getDistance>31.350397116680228
Searching Web ServicesSearching Web Services
Xin (Luna) Dong, Alon Halevy, Dinh Lam, Xin (Luna) Dong, Alon Halevy, Dinh Lam, Jayant Madhavan, Ema Nemes, Jun ZhangJayant Madhavan, Ema Nemes, Jun Zhang
University of WashingtonUniversity of Washington
www.cs.washington.edu/wooglewww.cs.washington.edu/woogle
Example ClustersExample Clusters (temperature, heatindex, icon, chance, precipe, uv, like, (temperature, heatindex, icon, chance, precipe, uv, like,
temprature, dew, feel, weather, wind, humid, visible, temprature, dew, feel, weather, wind, humid, visible, pressure, condition, windchill, dewpoint, moonset, sunrise, pressure, condition, windchill, dewpoint, moonset, sunrise, moonrise, sunset, heat, precipit, extend, forecast, china, moonrise, sunset, heat, precipit, extend, forecast, china, local, update)local, update)
(entere, enter, pitcher, situation, overall, hit, double, strike, (entere, enter, pitcher, situation, overall, hit, double, strike, stolen, ball, rb, homerun, triple, caught, steal, pct, op, slug, stolen, ball, rb, homerun, triple, caught, steal, pct, op, slug, player, bat, season, stats, position, experience, throw, player, bat, season, stats, position, experience, throw, players, draft, experier, birth, modifier)players, draft, experier, birth, modifier)
(state, city)(state, city) (zip)(zip) (code)(code)
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Recall
Precision Func
Comb
ParOnly
Woogle
Impact of Multiple Sources of Evidences Impact of Multiple Sources of Evidences in Operation Matchingin Operation Matching
Wooglewithout
clustering
Ignore structure
Text matching on descriptions