Algoritmo di text-similarity per l'annotazione semantica di Web Service

8/9/2019 Algoritmo di text-similarity per l'annotazione semantica di Web Service

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SWAP research group - 27 luglio 2010

Michele Filannino, @bronko85

Algoritmo di text-similarityper lannotazione semantica di WS

luned 23 agosto 2010


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OutlineIl problema

Scenario di riferimento

Similarit

SAWA

Word-to-word similarity

Text-to-text similarity

Risultati sperimentali

Qualit dei risultati

Tempo di esecuzione

Sviluppi futuri

Sessione dimostrativa2



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Il problemaCome misurare la similarit tra due testi?



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Scenario di riferimento

WSDL file CODEArchitectsAnnotation Tool

Natural languagedescriptions

SAWSDL fileCODEArchitectsAnnotation Tool

To approve/rejectsuggested annotations

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Similarit semantica

Assegnare una metrica di somiglianza, basata sul significato, ad un insieme di

termini e/o documenti;

Similarit Correlativit;

Banca e denaro sono correlati sebbene non siano affatto simili;

Similarit Correlativit;

Ragazza e fanciulla sono simili quindi anche correlati.

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Similarit semantica in SWOP

Concetti del WS

- RequestOrder

- Order

- BillingInformation

- ...

Concetti ontologici

Order -

OrderNumber -

OrderID -

BillID -

BillReference -

BusinessFirm -Product -

Catalog -

... -

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Peso computazionale

Esempio:

Ontologia con 1200 concetti

WSDL con 15 annotazioni

1.200 x 15 = 18.000 esecuzioni di SAWA

7

:(



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SAWASimilarity Algorithm Wikipedia-bAsed



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Word-to-word similarity

Date due parole stabilire quanto esse sono simili;

Tipi di algoritmi per il calcolo della similarit tra parole:

Corpus-based: pointwise mutual information, latent semantic analysis;

Hierarchy-based: Leacock & Chodorow, Lesk, Wu & Palmer, Resnik, Lin, Jiang &

Conrath;

Input: due parole;

Output: score compreso tra 0 e 1.

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Algoritmo di Lin (1998)10



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Tool di word-to-word similarity

Libreria utilizzata: LinguaTools DISCO;

Utilizza Wikipedia come gerarchia di concetti

202.578 concetti;

Aggiornato al 1 gennaio 2008

Utilizza lalgoritmo di Lin per il calcolo della similarit.

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Esempi

Tiger, lion = 90%

Doctor, nurse = 70%

Stock, market = 47%

Love, sex = 46%

FBI, investigation = 35%

Professor, cucumber = 0,006%

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Qualit dellalgoritmo

Corpus per la misurazione della qualit: WordSim353;

Coefficienti di correlazione (Pearson):

Wikipedia: 0,574;

BNC: 0,415;

PubMed: 0,105;

0

22,500

45,000

67,500

90,000



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Text-to-text similarity

Dati due testi stabilire quanto essi sono simili;

Estensione opportuna degli algoritmi di word-to-word similarity;

Rimozione delle parole (stopword)

basso potere discriminatorio;

alta frequenza di occorrenza;

Input: due testi;

Output: score compreso tra 0 e 1.

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Stopword

name customer categorized individual consumer

Returns the first and last name of each customer who is categorized as an

individual consumer

STOPWORD

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Algoritmo di Corley & Mihalcea(2005)16



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Ottimizzazioni (v1.2)

Caching delle frequenze di ogni termine;

Caching delle similarit tra termini;

Apprendimento incrementale;

Riduzione degli accessi a DISCO;

Performance ridotte di 10 volte;



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Risultati sperimentaliQualit e tempo di esecuzione



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DESCRIZIONE DEL DOCUMENTO WSDL SCELTA:

"returns the first and last name of each customer who is categorized as an individual consumer"

RANKING DEI CONCETTI ONTOLOGICI SIMILI (con relativo score):

*---------------------------------------------------------------------------------------------------------------*

| Descrizione | Score |*---------------------------------------------------------------------------------------------------------------*

| name: name of customer | 62,85% |

| customer: Current customer individual information | 56,91% |

| customeraddress: Customer address | 42,36% |

| customercredicard: Customer credit card information | 35,08% |

| salesreason: Reasons why a customer may purchase a particular product. | 30,35% |

| customerstore:Stores of our Company (customer and resellers). | 17,31% |

| salesorderdetail: Product details associated with a specific sales order. | 2,99% |

| productinventory: Product inventory information. | 2,59% |

| salesrepresentativeperson: Contains current sales information for the sales representative persons. | 2,39% |

| productlocation: Product manufacturing locations | 2,36% |

| salestaxrate: Sales Tax rate. | 2,36% |

| salesterritory: Sales territory. | 2,22% || employeeaddress: Employee information such as salary, department, and title. | 2,18% |

| product: Products sold or used in the manfacturing of sold products. | 2,12% |

| enterpricedepartment: Departments of Enterprise | 2,00% |

| salesspecialoffer: Sales Special Offer (discounts). | 1,99% |

| productlistpricehistory: Changes in the list price of a product over time. | 1,80% |

| shipmethod: Shipping methods. | 1,79% |

| salesorder: General sales order information (header). | 1,76% |

| productdocument: Product Document | 1,73% |

| productcosthistory: Changes in the cost of a product over time. | 1,68% |

| productbillofmaterials: Bill Of Materials are items required to make products and product subassembl | 1,61% |

| productmodel: Product model classification. | 1,48% |

| currencyrate: Currency exchange rates. | 1,40% |

| salesshoppingcartitem: Contains shopping cart items until the order is submitted or cancelled. | 1,29% || productcategory: High-level product categorization. | 1,27% |

| addresstype: Types of addresses | 0,95% |

| unitmeasure: Unit of measure. | 0,80% |

| currency: Standard ISO currencies. | 0,51% |

| countryregion: ISO standard codes for countries and regions. | 0,51% |

| stateprovince: States and provinces | 0,12% |

*---------------------------------------------------------------------------------------------------------------*

Time elapsed: 9.4 seconds.19



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"lists the names and addresses of all individual customers"


*---------------------------------------------------------------------------------------------------------------*













| salesterritory: Sales territory. | 2,14% || salesrepresentativeperson: Contains current sales information for the sales representative persons. | 2,08% |

| employeeaddress: Employee information such as salary, department, and title. | 1,81% |


| productlocation: Product manufacturing locations | 1,78% |




| currencyrate: Currency exchange rates. | 1,46% |




| salesshoppingcartitem: Contains shopping cart items until the order is submitted or cancelled. | 1,36% |

| productbillofmaterials: Bill Of Materials are items required to make products and product subassembl | 1,32% || productdocument: Product Document | 1,27% |


| productcategory: High-level product categorization. | 1,01% |




*---------------------------------------------------------------------------------------------------------------*




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"returns the name of each customer that is categorized as a store"


*---------------------------------------------------------------------------------------------------------------*








| employeeaddress: Employee information such as salary, department, and title. | 2,75% |




| salesterritory: Sales territory. | 2,19% |

| salesrepresentativeperson: Contains current sales information for the sales representative persons. | 2,09% || productlocation: Product manufacturing locations | 1,91% |






| productdocument: Product Document | 1,63% |

| salesshoppingcartitem: Contains shopping cart items until the order is submitted or cancelled. | 1,61% |


| productbillofmaterials: Bill Of Materials are items required to make products and product subassembl | 1,47% |



| currencyrate: Currency exchange rates. | 1,30% || productcategory: High-level product categorization. | 1,15% |






*---------------------------------------------------------------------------------------------------------------*




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Tempo di esecuzione

3

6

5

7

2

8

1

4

0 12,5 25 37,5 50

Ottimizzato Non ottimizzato

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Sviluppi futuriImminenti e futuri



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Imminenti:

Realizzazione dellinterfaccia Web Service

Realizzazione dellinterfaccia Web (gratuita)

Realizzazione dellinterfaccia di rete

Disseminazione scientifica

Altri:Introduzione di soglie per migliorare le performance

Rilascio con licenza open-source del codice sorgente

Sviluppi futuri



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Sessione dimostrativa

Documents

Algoritmo di text-similarity per l'annotazione semantica di Web Service