Web Service Discovery via Example Query Distance Metrics
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In a web service-oriented architecture, identifying and communicating with the correct web service is challenging due to the lack of global standards and the complexity of XML schema differences between providers and consumers, leading to difficulties in creating compatible queries.
Innovation Solution
A system and method that allows web service consumers to create an example XML query, compare it element-by-element with available web services, and quantify differences using a distance metric to identify the closest matching web service, which can then be used to automatically or manually rewrite the query to match the required schema.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If web service consumers use traditional name and keyword-based search schemes to locate web services, then the search process is simple, but the ability to handle schema differences and find compatible services is poor
Solution Approach 1:
The patent introduces an intermediary system that acts as a mediator between the web service consumer and the web service provider. This intermediary compares the consumer's example query against available web services, quantifies differences using distance metrics, and helps translate queries to match different schemas. The intermediary handles the complexity of schema differences without requiring the consumer to directly manage schema compatibility issues.
Solution Approach 2:
The patent changes the parameter of query comparison from traditional exact matching to quantified difference measurement. By using distance metrics that can handle various types of differences (synonyms, hyponyms, structural variations), the system allows flexible matching beyond exact schema compatibility, enabling consumers to work with services that have different but compatible schemas.
2Measurement precision
If web service consumers manually create XML queries matching precise schemas, then query accuracy is high, but the complexity and time required increases significantly
Solution Approach 1:
The patent performs preliminary action by pre-comparing example queries against multiple web services and pre-calculating distance metrics before the actual query execution. This preliminary comparison and ranking allows the consumer to identify compatible services in advance, reducing the complexity of manual query creation and adjustment during actual usage.
Solution Approach 2:
The patent uses the concept of copying by creating an example query that represents the consumer's needs in a simplified form, then using this example to automatically generate or select appropriate XML queries for different web services. The example query serves as a template that can be adapted to match different schemas without requiring the consumer to manually create each specific query.
3Adaptability or versatility
If the system compares example queries with web services element-by-element using distance metrics, then the ability to handle schema variations is improved, but the computation time increases
Solution Approach 1:
The patent segments the query comparison process into discrete elements, comparing each element of the example query against corresponding elements in web services independently. This segmentation allows for systematic handling of schema variations through distance metrics while enabling optimization at each segment level, potentially reducing overall computation time through early elimination of clearly incompatible services.
Data Source
AI summary
A system, method, and computer program product allows a web service consumer to create an example query which illustrates the web service desired. The example query is compared, element by element, to potentially relevant web services. The difference between each element in the example query and any element in the web service being compared is quantified as a distance metric, based on the relationship between the elements. The relationships might be classified as: exact match, direct synonym, fuzzy synonym, hyponym, hypernym, or no match. The distance metric for each element in the example query is summed to calculate a total distance between the example query and the web service being compared. This sum is an expression of the difference between the example query and the web service being compared.