毕业论文报告 孙悦明 2012.04
论文题目 使用本体结构辅助系统化调研
提纲 论文工作介绍 系统化调研简介 结构化摘要简介 工作整体介绍 SLRONT的构建 扩展SLRONT为COSONT 实例化COSONT
系统化调研简介 系统化调研 SLR Protocol 定义研究问题 各个步骤的执行准则 Identification of Research Study Selection Study Quality Assessment Data Extraction Data Synthesis
结构化摘要简介 结构化摘要 完备性与清晰性 Background Object Method Result Conclusion
工作整体介绍 工作流程图
SLRONT的构建 Review Protocol部分
SLRONT的构建 Primary Study部分
扩展为COSONT 主要扩展Structured abstract部分
COSONT 估算方法部分的扩展
实例化COSONT—非结构化摘要 Background Method Conclusion part
实例化COSONT—基于规则的分析 MAINSEN CONCLU 定位结果 R1: S = PP, NP VP R2: S = NP VP In this paper, we propose an approach that converts cost estimation into a classification problem and that classifies new software projects in one of the effort classes, each of which corresponds to an effort interval. MAINSEN R1: S = PP, NP VP R2: S = NP VP CONCLU R3: S = (PP,)+ NP VP 定位结果 Results of the study show a significant correlation between the software development effort and all three models. Sentences Total Found Precision MAINSEN Sentence 347 267 76.95% CONCLU Sentence 244 70.3%
实例化COSONT—抽取本体信息 抽取的名词词组对比 抽取结论 - amod(method-9, effective-8) The results show that KNN is an effective method. - amod(method-9, effective-8) - nsubj(method-9, KNN-5) - cop(method-9, is-6) - det(method-9, an-7) Paper Manual Auto Aver Recall per paper Student 1 85 652 508 80.102% Student 2 406 342 84.281% Student 3 472 336 72.428% Student 4 503 390 77.613% This paper describes a controlled experiment of student programmers performing maintenance tasks on a C++ program.
实例化COSONT
支持SLR中的关键步骤 辅助系统化调研第二步 寻找带有regression and neural network的文章 专家判断： 自动化方法 Student ID Num of Papers Paper Identified Time (Person*Hour) 1 87 6 8.5 2 7.5 3 9 4 86 10 Total 347 11 35
Q&A
感谢各位老师和同学！ 2012.04