Agent-based web search personalization approach using dynamic user profile

Moawad, Ibrahim F.; Talha, Hanaa; Hosny, Ehab; Hashim, Mohamed

doi:10.1016/j.eij.2012.09.002

Cited by 26 publications

(9 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A new approach base on multi agent system for web search results personalisation. The proposed approach (Moawad et al, 2012) introduces a model to build a user profile from initial and basic information and maintain it through implicit user feedback to establish a complete, dynamic and update user profile. In the web search process, the model semantically optimises the user query in two steps: query optimisation using user profile preferences and query optimisation using the Word Net ontology.…”

Section: User Profile Approachesmentioning

confidence: 99%

Web service selection based on QoS and user profile

2020

View full text Add to dashboard Cite

The web services are from different sources, heterogeneous, and of large volume. The user is in a crucial situation to select the best web services. The web service selection process aims to discovery the desired web services; as it allows to select the best web services to users' query. In particular, various web services have the same functionalities, so we need another factor to select the desired web services, which is the quality of service (QoS). The QoS has an important role in the web service selection process, it aims to classify the web service that have same functionality. This paper focuses on different concepts of the QoS. We present a new approach that is composed by two services; its role is primarily the best web service selection in relation with users' query and profile. In our approach, a better knowledge of user behavior is important because users can participate in research design and construction. The experiment shows that our method can accurately recommend the needed web services in a faster time.

show abstract

Section: User Profile Approachesmentioning

confidence: 99%

Web service selection based on QoS and user profile

2020

View full text Add to dashboard Cite

show abstract

“…Web personalization has been the subject of several research efforts [30][31][32][33]. Online merchants and many organizations are increasingly using this alternative to deliver customer value and achieve lucrative growth using sophisticated personalization tools; many of them are cloud-based [34].…”

Section: Web and Cloud Services Personalizationmentioning

confidence: 99%

On personalized cloud service provisioning for mobile users using adaptive and context-aware service composition

et al. 2018

View full text Add to dashboard Cite

Cloud service providers typically compose their services from a number of elementary services, which are developed in-house or built by third-party providers. Personalization of composite services in mobile environments is an interesting and challenging issue to address, given the opportunity to factor-in diverse user preferences and the plethora of mobile devices at use in multiple contexts. This work proposes a framework to address personalization in mobile cloud-service provisioning. Service personalization and adaptation may be considered at different levels, including the user profile, the mobile device in use, the context of the user and the composition specification. The user's mobile device and external services are typical sources of context information, used in our proposed algorithm to elicit context-aware services. The selection process is guided by quality-of-context criteria that combine cloudservice provider requirements and user preferences. Hence, the paper proposes an integrated framework for enhancing personalized mobile cloud-services, based on a composition approach that adapts context information using a common model of service metadata specification.

show abstract

“…Here global best solution ( g best) of the particle is the best solution found in the neighborhood and the personal best solution ( l best) is the best position visited by the particle which until now are used to find the particles new position. Moawad et al [ 12 ] introduced a new multiagent system based approach for personalizing the web search results. In this approach dynamic user profiles are created and maintained through implicit user feedback system.…”

Section: Literature Surveymentioning

confidence: 99%

A Dynamic Recommender System for Improved Web Usage Mining and CRM Using Swarm Intelligence

Alphy

Prabakaran

2015

The Scientific World Journal

View full text Add to dashboard Cite

In modern days, to enrich e-business, the websites are personalized for each user by understanding their interests and behavior. The main challenges of online usage data are information overload and their dynamic nature. In this paper, to address these issues, a WebBluegillRecom-annealing dynamic recommender system that uses web usage mining techniques in tandem with software agents developed for providing dynamic recommendations to users that can be used for customizing a website is proposed. The proposed WebBluegillRecom-annealing dynamic recommender uses swarm intelligence from the foraging behavior of a bluegill fish. It overcomes the information overload by handling dynamic behaviors of users. Our dynamic recommender system was compared against traditional collaborative filtering systems. The results show that the proposed system has higher precision, coverage, F1 measure, and scalability than the traditional collaborative filtering systems. Moreover, the recommendations given by our system overcome the overspecialization problem by including variety in recommendations.

show abstract

Agent-based web search personalization approach using dynamic user profile

Cited by 26 publications

References 13 publications

Web service selection based on QoS and user profile

Web service selection based on QoS and user profile

On personalized cloud service provisioning for mobile users using adaptive and context-aware service composition

A Dynamic Recommender System for Improved Web Usage Mining and CRM Using Swarm Intelligence

Contact Info

Product

Resources

About