论文外文文献.doc

论文外文文献
河北地质大学
本科生毕业设计(论文)
外文翻译
题目基于西瓜预测的多种线性模型算法探究姓名学号 4********** 学院信息工程学院专业软件工程指导教师
2016年 5月 28日
英文文献:
A logistic regression model for Semantic Web
service matchmaking
Abstract
Semantic Web service matchmaking, as one of the most challenging problems in Semantic Web services (SWS), aims to filter and rank a set of services with respect to a service query by using a certain matching strategy. In this paper, we propose a logistic regression based method to aggregate several matching strategies instead of a fixed integration (., the weighted sum) for SWS matchmaking. The logistic regression model is trained on training data derived from binary relevance
assessments of existing test collections, and then used to predict the
probability of relevance between a new pair of query and service according to their matching values obtained from various matching strategies. Services are then ranked according to the probabilities of relevance with respect to each query. Our method is evaluated on two main test collections, SAWSDL-TC2 and Jena Geography Dataset(JGD).
Experimental results show that the logistic regression model can effectively predict the relevance between a query and a service, and hence can improve the effectiveness of service matchmaking.
Keywords:Semantic Web service, matchmaking, logistic regression
1 Introduction
Semantic Web services