Name
Abstract | ||
|---|---|---|
We present a novel knowledge-based approach for automated electronic barter trade systems. An e-barter is basically a closed e-marketplace, where agents may exchange (buy/sell) goods ---or equivalent trade dollars--- only with other participants to the e-barter. Obviously, in such systems one of the major issues is keeping exchanges as balanced as possible. If the description of goods or services to be exchanged is simple and limited to a well defined set, e.g. , oil, wheat, transport, etc., then an exchange based only on price and quantity is enough. But, what if goods or services to be exchanged are described in a complex way? Is it a suitable exchange the one involving mobile phones supporting video streaming with a QWERTY keyboard if the agent is looking for smart phones ? Those two descriptions, although very different form a syntactic point of view, are very similar with respect to their meaning (semantics). How could an agent manage and exploit the knowledge on a given domain to deal with such a semantic information and optimize exchanges? We focus on how to find most promising matches, in a many-to-many matchmaking process, between bids (supplies/demands), taking into account not only the price and quantities as in classical barter trade systems, but also a semantic similarity among bid descriptions while keeping exchanges balanced. To this aim we use a logical language to express agent preferences, thereby enhancing bid expressiveness. We also define a logic-based utility function that allows to evaluate the semantic similarity between bids. Finally we illustrate the optimization problem we solve in order to clear the market. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-93920-7_9 | DALT |
Keywords | Field | DocType |
semantic similarity,automated electronic barter trade,agent preference,suitable exchange,bid description,equivalent trade dollar,bid expressiveness,balanced e-barter trading,semantic information,classical barter trade system,optimize exchange,knowledge base,optimization problem | Semantic similarity,Barter,Computer science,Operations research,Knowledge management,Description logic,Exploit,Artificial intelligence,Mobile phone,Optimization problem,Syntax,Semantics | Conference |
Volume | ISSN | Citations |
5397 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 19 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Azzurra Ragone | 1 | 511 | 40.86 |
| Tommaso Di Noia | 2 | 1857 | 152.07 |
| Eugenio Sciascio | 3 | 25 | 3.02 |
| Francesco M. Donini | 4 | 3481 | 452.47 |