A Mediation Architecture for Global Comparison Services

A Mediation Architecture for Global Comparison Services

Hongwei Zhu (Old Dominion University, USA) and Stuart E. Madnick (Massachusetts Institute of Technology, USA)
Copyright: © 2009 |Pages: 18
DOI: 10.4018/978-1-59904-978-6.ch003

Abstract

Global comparison services facilitate easy comparison of product offerings around the world. To offer such services, one has to address the semantic heterogeneity problems that often arise when data is collected from sources around the world. In this chapter, the authors use examples to illustrate three types of semantic heterogeneity problems that a global comparison service may encounter. Then they present a mediation architecture as a solution to addressing these problems. The feasibility of using the architecture to enable global comparison is demonstrated with a prototype application. An evaluation of the solution shows that it is scalable due to its capability of automatically generating necessary conversions from a small set of predefined ones.
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Motivating Example

Imagine for the moment you are from Sweden and interested in buying a pocket sized digital camcorder. After some research on the Web you decide to buy a SONY MICROMV DCR-IP5, which records video in MPEG format for easy editing on computers and weighs only 0.336 kilograms (i.e., 12 ounces). You use your favorite comparison service Kelkoo (at www.kelkoo.se) to find the best deals and it returns information as shown in Figure 1.

Figure 1.

Price data displayed by a comparison aggregator in Sweden

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Among the vendors found, 18,082 Swedish krona (SEK) is the lowest total price (see the Totalpris column in Figure 1). Is this the best deal, or is there a substantially better deal, on a global basis? If you plan to use the camcorder while on an upcoming trip to several countries, is it better to buy it in Sweden before the trip or buy it at the first stop (say, the U.S.) on your arrival? Without a global comparison service, this can only be done manually by visiting numerous regional comparison aggregators available in other countries. Our manual exercise found one vendor in the U.S. sells the product for $999.99, and you can add $100 to have it shipped to you in Sweden.

Between 18,082 SEK and $1,099.99, which is the better deal? Information, such as knowing that 1 US dollar is around 10 SEK (at the time), will be useful in answering the question, but such information usually is not readily available from a regional aggregator. After this information is obtained, for example by querying a currency conversion service, such as www.oanda.com, we can use it to convert the prices into the same currency. Only after all these steps have been done do we know that the Swedish offer is 64% more expensive than the U.S. offer.

As seen in the example, there are certain “inconveniences” when comparing prices globally: a user has to visit and collect data from multiple sites, determine if the data needs to be converted to reconcile the differences (e.g., currencies and inclusion or exclusion of taxes), and perform the conversions to make the comparison meaningful. This process is time consuming and error prone. A global comparison service could alleviate the user from these tedious tasks. Such a service provider would need to ensure that the information is properly processed so that data coming from different parts of the world can be correctly interpreted by users who are also geographically dispersed around the world. The users of such services can be consumers (looking for the best deals), vendors (developing competitive pricing strategies), manufacturers (monitoring vendor pricing behaviors), arbitragers (buying low at one place and selling high at another), and economists (studying the global markets).

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