Hybrid Recommendation in Intermodal Transportation--论文代写范文精选

交通管理涉及不同的决策问题,它基本上是合适的路线和相关载体的选择。这类问题主要是提高由于各种各样的客户的偏好(如成本限制,加载偏好,交付日期)和承运人的服务资源(如交通媒体,可用行程,容量)。下面的essay代写范文将进行详述。

Abstract 
Diverse recommendation techniques have been already proposed and encapsulated into several e-business applications, aiming to perform a more accurate evaluation of the existing information and accordingly augment the assistance provided to the users involved. This paper reports on the development and integration of a recommendation module in an agent-based transportation transactions management system. The module is built according to a novel hybrid recommendation technique, which combines the advantages of collaborative filtering and knowledge-based approaches. The proposed technique and supporting module assist customers in considering in detail alternative transportation transactions that satisfy their requests, as well as in evaluating completed transactions. The related services are invoked through a software agent that constructs the appropriate knowledge rules and performs a synthesis of the recommendation policy. 
Key words: Data mining, Knowledge Association Rules, Recommender systems, Intermodal Transportation.

Introduction 
Transportation management involves diverse decision making issues, which are basically related to the appropriate route and carrier selection. Such issues mainly raise due to the variety of the customer’s preferences (e.g. cost limitations, loading preferences, delivery dates) and the carrier’s service resources (e.g. transportation media, available itineraries, capacity). The matching between the above preferences and offered services cannot be easily handled manually, as in most cases a plethora of alternative options exist, while time and money limitations are ubiquitous. 

Generally speaking, transportation transactions management requires quick and cost-effective solutions to the customers’ demands for both distribution and shipping operations. In cases where many alternatives exist, there is an urgent need for providing recommendations. The customer should be assisted in order to properly evaluate the proposed alternatives and make his/her final decision. Recommendation systems have been described as systems that produce individualized recommendations or have the effect of guiding the user in a personalized way, in environments where the amount of on-line information vastly outstrips any individual’s capability to survey it [2]. Generally speaking, such systems represent the users’ preferences for the purpose of submitting suggestions for purchasing or evaluating elements. Fundamental applications can be found in the fields of electronic commerce and information retrieval, where they provide suggestions that effectively direct the users to the elements that satisfy better their necessities and preferences [21].

Conclusions 
This paper has elaborated a series of issues related to the integration of hybrid recommendation techniques into an agent–based transportation transactions management platform. We proposed a hybrid recommendation module that combines different recommendation techniques in order to provide the user with more accurate and efficient suggestions. The overall recommendation process is coordinated by a software agent, which is responsible for carrying out multiple tasks, such as coordination of the recommendation module, selection of alternatives and knowledge synthesis through the exploitation of different recommendation techniques and algorithms. The presence of the Recommender Agent guarantees that the user will be provided with continuous recommendations, which are dynamically updated. Finally, we have exploited concepts related to Web Services in order to make the proposed recommendation functionalities accessible from external applications. 

Future work plans mainly concern the consideration of additional recommendation techniques, such as content– based or model–based techniques and the exploitation of data mining algorithms in order to enhance the overall quality of the recommendations provided. The development of additional (local or remote) Web Services, which will be capable of carrying out more complex requests for recommendation techniques synthesis, is another major concern.（essay代写)

51Due网站原创范文除特殊说明外一切图文著作权归51Due所有；未经51Due官方授权谢绝任何用途转载或刊发于媒体。如发生侵犯著作权现象，51Due保留一切法律追诉权。（essay代写)
更多essay代写范文欢迎访问我们主页 www.51due.com 当然有essay代写需求可以和我们24小时在线客服 QQ:800020041 联系交流。-X（essay代写)