A Framework for Web Services Retrieval Using Bio Inspired Clustering Anirudha R C Siddhartha R Thota Avinash N Bukkittu and Sowmya

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A Framework for Web Services Retrieval Using

Bio Inspired Clustering

Anirudha R C, Siddhartha R Thota, Avinash N Bukkittu, and Sowmya

Kamath S

Department of Information Technology, National Institute of Technology Karnataka,

Mangalore, India, 575025

{rcanirudha,sddhrthrt,avinashnb141}@gmail.com,sowmyakamath@nitk.ac.in

Abstract. Eﬃciently discovering relevant Web services with respect to

a speciﬁc user query has become a growing challenge owing to the incred-

ible growth in the ﬁeld of web technologies. In previous works, diﬀerent

clustering models have been used to address these issues. But, most of

the traditional clustering techniques are computationally intensive and

fail to address all the problems involved. Also, the current standards fail

to incorporate the semantic relatedness of Web services during cluster-

ing and retrieval resulting in decreased performance. In this paper, we

propose a framework for web services retrieval that uses a bottom-up,

decentralized and self organising approach to cluster available services.

It also provides online, dynamic computation of clusters thus overcoming

the drawbacks of traditional clustering methods. We also use the seman-

tic similarity between Web services for the clustering process to enhance

the precision and lowerthe recall.

Keywords: Web services, Semantic similarity, ﬂocking model, cluster-

ing

1 Introduction

In recent years, there has been a massive growth in the ﬁeld of web technolo-

gies as organizations are increasingly moving towards providing services to their

consumers over the Web. This has resulted in an increase in the number of Web

services and applications using these services in e-commerce, travel and other

domains are also growing exponentially. This in turn creates a huge demand for

several techniques for eﬃciently ﬁnd the Web services.

UDDI Universal Business Registries (Universal Discovery, Description and

Integration) which were intended to be a standard for publishing and ﬁnding

web services has been shut down in 2005 due to lack of popularity. The main

aim of the public UDDI initiative was to allow users and applications alike to

ﬁnd Web services through keyword searches. However, the number of Web ser-

vices retrieved based on purely syntactic keyword searches can be quite large

and most of search results were irrelevant to users, resulting in lower precision

and high recall values. This is because keywords are described in natural lan-

guage which has free form and provides ample scope for ambiguity in terms of

arXiv:2210.01761v1 [cs.LG] 4 Oct 2022

2 Web Services Retrieval Using Bio Inspired Clustering

meaning and context. Syntactically diﬀerent words can be semantically similar

(synonyms). Likewise, semantically diﬀerent words can be syntactically similar

(homonyms). Keyword based searches do not capture the underlying semantics

of Web services. The limitations of syntax based Web service discovery paved the

way for research involving semantics for search and retrieval of Web services. A

semantic approach is intuitive in the sense that it tries to meaningfully discover

relevant Web services.

Various studies have shown clustering to be a more eﬀective way for dis-

covery of Web services. But as the Web services are ever increasing in number,

incorporating a static clustering algorithm for their discovery demands the re-

computation of all the clusters every time a new service is added. Due to the

highly computationally intensive nature of performing semantic comparison be-

tween Web services, the use of such techniques is not feasible. This calls for

a clustering technique which can easily accomodate newly added Web services

without the need for signiﬁcant recomputation of already formed clusters. Pre-

viously such dynamic algorithms have been proposed to handle the problems

of large datastreams like network packet ﬂow, clickstream data, etc. This paper

presents a framework to incorporate a similar dynamic algorithm for Web service

discovery.

In order to address the issues around the discovery and retrieval of Web

services, we propose a framework which is based on bio-inspired clustering to

cluster available services dynamically to facilitate their eﬃcient retrieval. The

proposed model is inspired by the bio-inspired FlockStream Algorithm proposed

by Foresterio et al [1] which proposes a model to compute clusters on the ﬂy

without aﬀecting the previously formed clusters. Adapting this technique for

clustering Web services addresses the problems of recomputation of all clusters.

Also, we include the concept of semantic similarity between the services ensuring

better precision and recall during retrieval. Furthermore, we also describe a

technique to retrieve the required Web services from these clusters based on the

creation of a virtual Web service formed using tags from the requirements given

by the user as a query for retrieval. We refer to this as a virtual boid or virtual

agent.

The rest of the paper is organised as follows: In Section 2 we discuss related

work in the domain of clustering web services. Section 3 presents a detailed

discussion on the proposed framework, describing the steps involved in the clus-

tering process. Finally, Section 4 concludes the paper along with scope for future

work in the proposed framework.

2 Related Work

Much research has been carried out in the area of discovery of Web services.

Of them clustering for reducing the search space for relevant service retrieval

has gained much popularity in recent years. In this section, we provide a brief

overview of existing research in the domain of clustering of Web services.

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AFrameworkforWebServicesRetrievalUsingBioInspiredClusteringAnirudhaRC,SiddharthaRThota,AvinashNBukkittu,andSowmyaKamathSDepartmentofInformationTechnology,NationalInstituteofTechnologyKarnataka,Mangalore,India,575025{rcanirudha,sddhrthrt,avinashnb141}@gmail.com,sowmyakamath@nitk.ac.inAbstract.Ecient...

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A Framework for Web Services Retrieval Using Bio Inspired Clustering Anirudha R C Siddhartha R Thota Avinash N Bukkittu and Sowmya

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