- -

A recommendation framework based on automated ranking for selecting negotiation agents. Application to a water market

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

A recommendation framework based on automated ranking for selecting negotiation agents. Application to a water market

Show simple item record

Files in this item

dc.contributor.advisor Ramírez Quintana, María José es_ES
dc.contributor.advisor Bella Sanjuán, Antonio es_ES
dc.contributor.author DURA GARCIA, ENCARNACIO MARIA es_ES
dc.date.accessioned 2012-05-25T09:53:31Z
dc.date.available 2012-05-25T09:53:31Z
dc.date.created 2011-09
dc.date.issued 2012-05-25
dc.identifier.uri http://hdl.handle.net/10251/15875
dc.description.abstract This thesis presents an approach which relies on automatic learning and data mining techniques in order to search the best group of items from a set, according to the behaviour observed in previous groups. The approach is applied to a framework of a water market system, which aims to develop negotiation processes, where trading tables are built in order to trade water rights from users. Our task will focus on predicting which agents will show the most appropriate behaviour when are invited to participate in a trading table, with the purpose of achieving the most bene cial agreement. This way, a model is developed and learns from past transactions occurred in the market. Then, when a new trading table is opened in order to trade a water right, the model predicts, taking into account the individual features of the trading table, the behaviour of all the agents that can be invited to join the negotiation, and thus, becoming potential buyers of the water right. Once the model has made the predictions for a trading table, the agents are ranked according to their probability (which has been assigned by the model) of becoming a buyer in that negotiation. Two di erent methods are proposed in the thesis for dealing with the ranked participants. Depending on the method used, from this ranking we can select the desired number of participants for making the group, or choose only the top user of the list and rebuild the model adding some aggregate information in order to throw a more detailed prediction. es_ES
dc.format.extent 73 es_ES
dc.language Inglés es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Recommendation es_ES
dc.subject Ranking based on probabilities es_ES
dc.subject Data mining es_ES
dc.subject Noegotiation es_ES
dc.subject Estimation trees es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.subject.other Máster Universitario en Ingeniería del Software, Métodos Formales y Sistemas de Información-Màster Universitari en Enginyeria del Programari, Mètodes Formals i Sistemes D'Informació es_ES
dc.title A recommendation framework based on automated ranking for selecting negotiation agents. Application to a water market es_ES
dc.type Tesis de máster es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Servicio de Alumnado - Servei d'Alumnat es_ES
dc.description.bibliographicCitation Dura Garcia, EM. (2011). A recommendation framework based on automated ranking for selecting negotiation agents. Application to a water market. http://hdl.handle.net/10251/15875 es_ES
dc.description.accrualMethod Archivo delegado es_ES


This item appears in the following Collection(s)

Show simple item record