Bio-Inspired Hybrid Algorithm for Web Services Clustering DOI: http://dx.doi.org/10.5772/intechopen.85200

Work

12

Liang

WSDL

Incremental

algorithm

Bisecting K-means

 K-means

No

 Tree-based

matching

 structure

352

 Xmethods.c

This approach clusters Web

The similarity approach is

not semantic, and the

clustering method is not bio-

inspired

service documents

om

Bindingpoint.c

om

Webservice

list.com

Xignite.com

et al. [1]

Platzer

WSDL

Statistical clustering analysis

 No

 Euclidean distance

 275

 Xmethods.c

This approach clusters Web

The clustering method is not

Advanced Analytics and Artificial Intelligence Applications

based on novel bio-inspired

algorithms.

Similarity measure is not

semantic

The semantic similarity does

not use a lexical database to improve similarity measures

service documents

om

et al. [2]

Pop

WSDL

Particle swarm and ant-

Yes

 Semantic similarity

894

collection

similar to the approach described in this chapter. The

main difference is on the

algorithms utilized

SAWSDL-TC

The solution approach is very

> by evaluating the

Degree of Match

(DoM)

et al. [3]

documents

based service clustering

> extracted from

OWL-TC4

Du et al.

WSDL

Bottom-up hierarchical

No

 Semantic similarity

1075

 OWL-TC4

This work is closely related with

The clustering method is not

based on novel bio-inspired

algorithms

collection

the approach presented in this

chapter

based on WordNet

clustering

[4]

documents

extracted from

OWL-TC4

Wu

WSDL

K-means

No

 The similarity

15,968

 Seekda

 This approach clusters Web

The clustering method is not

based on bio-inspired

algorithms.

measure is not semantic The clustering method is not

applied to Web services

 Similarity

service documents

integrates all the

feature measures using a weighed sum

et al. [5] Prakash

Data is based on

Genetic Algorithm,

No

 Not specified

 Not for

No

The clustering approach is based

on novel bio-inspired

algorithms.

Web

services

Differential

Particle Swarm

 Evolution,

and

three real and

documents

documents

documents

 Input data

 Clustering approach

 Use of

Similarity

Number

Service

Benefits

Limitations

of Web

repository

services

used

ontologies

approach
