Conference Paper

On the Reputation of Agent-Based Web Services.

Conference: Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2010, Atlanta, Georgia, USA, July 11-15, 2010
Source: DBLP
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Available from: Jamal Bentahar, Aug 22, 2015
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    • "The main aim of this paper is to show the efficiency of the cuckoo search algorithm [5] in solving UCP and to propose a fresh MOCS to reject the role of the conclusion maker (system operator) in setting the reeling reserve in UCP. In MOUCP problem [12], is similar to other evolutionary process, cuckoo search algorithm begins with an initial frozen number of cuckoo nests [7]. At the end of every propagation of CSA, the size of cuckoo nests gains when compared to the sign number of nests. "
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    ABSTRACT: Web Service is an open standard based web applications that interact with other web applications for the reason of exchanging data. Web service is self telling service that will perform fine tasks and can be accessed through the web. Web services discovery have the Hyperlink-Induced Topic Search (HITS) linking analysis algorithm that rates Web pages. The increasing convolution of compositions and the ration of people and services involve adaptive and context-aware contact models. This method is an imperative for the internet penetrating techniques. But this emerging technique faces Topic drift problem which is a pitfall in web service discovery. This paper we introduce HYBRID algorithm to endorse Topic drift drawback. This algorithm is combination of Multi Objective Bat Algorithm (MOBA) and Multi objective cuckoo search (MOCS) algorithms .MOBA is used for the multi data access and the MOCS algorithm is used for fast access techniques .By using this HYBRID algorithm the efficiency and accuracy can be improved. So this technique is called as HYBRID algorithm (MOBA &MOCS). The experimental evaluation shows that this algorithm reduces topic drifting problem and increases the accuracy of the web services discovery.
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    • "However, in reputation systems, buyers may provide untruthful ratings to promote some sellers or drive some other sellers out of the market. In [5], a reputation mechanism with a controller agent as the reputation manager is proposed to detect fake positive ratings from collusive or dishonest buyers. Different incentive mechanisms have also been proposed to elicit truthful ratings from buyers. "
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    ABSTRACT: In e-marketplaces with limited inventory where buyers' demand is larger than sellers' supply, promoting honesty raises new challenges: sellers may behave dishonestly because they can sell out all products without the necessity of gaining high reputation; buyers may provide untruthful ratings to mislead other buyers in order to have a higher chance to obtain the limited products. In this paper, we propose a novel incentive mechanism to promote honesty in such e-marketplaces. More specifically, our mechanism models both buyer and seller honesty. It offers higher prices to the products provided by honest sellers so that the sellers can gain more profit. Honest buyers also have a higher chance to do business with honest sellers and are able to gain more utility. Theoretical analysis and experimental results show that our mechanism promotes both buyer and seller honesty. Finally, we address the re-entry problem by imposing membership fees on new sellers. We show that the membership fee can discourage sellers from re-entry both in theoretical analysis and experimental validation.
    14th International Conference on Electronic Commerce (ICEC); 01/2012
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    • "Thus, buying agents need a means to assess the quality of different sellers offering a particular product and select the most profitable seller who best meets the buyers' requirements. Reputation systems [1], [2], [3], [4] are a particularly effective approach for buyers to model sellers' reputation (representing their quality) based on the reporting of seller information provided by other buyers (also called advisers). These systems often assume that sellers have infinite (or very large) inventory and the number of high quality products provided by good sellers is unlimited. "
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    ABSTRACT: In a reputation system for multiagent based electronic marketplaces where the number of high quality products provided by good selling agents is unlimited, buying agents often share seller information without the need to consider possible utility loss. However, when those good sellers have limited inventory, buyers may have to be concerned about the possibility of losing the opportunity to do business with the good sellers if the buyers provide truthful information about sellers, due to the competition from other buyers. In this paper, we propose an adaptive mechanism built on a game theoretic basis for buyers to determine their optimal reputation reporting strategy, by modeling both the competency and willingness of other buyers in reporting seller reputation and strategically choosing reporting behaviours that maximize their utility according to the modeling results. The results of the experiments carried out in a simulated competitive e-marketplace confirm that our proposed mechanism leads to better utility for buyers in such an environment.
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