| 评估属性层知识和实例层知识融合效果的有效指标 |
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| 引用本文： | 周元珂,邵峰晶,吴舜尧.评估属性层知识和实例层知识融合效果的有效指标[J].青岛大学学报(自然科学版),2014(2):29-33,38. |
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| 作者姓名： | 周元珂 邵峰晶 吴舜尧 |
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| 作者单位： | [1]青岛大学信息工程学院,青岛266071 [2]青岛大学自动化工程学院,青岛266071 |
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| 基金项目： | 国家自然科学基金（批准号：91130035）资助;国家公益性行业科研专项基金（批准号：200905030-2）资助;山东省自然科学基金重点项目（批准号：ZR2012FZ003）资助;山东省自然科学基金（批准号：ZR2012FQ017）资助. |
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| 摘 要： | 并不是所有的先验知识都能提高聚类质量，因此，评估先验知识的质量对半监督聚类极其重要。在现有的可有效评估成对约束形式的实例层知识的指标——信息量和一致性基础上，提出了可有效评估属性排序形式的属性层知识的指标，即信息量和有效性。并证实了提出指标的有效性和潜力。
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| 关 键 词： | 半监督聚类 成对约束 属性排序 |
An Effective Measure to Evaluate the Fusion of Attribute-level and Instance-level Knowledge |
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| ZHOU Yuan-ke SHAO Feng-jing,WU Shun-yao.An Effective Measure to Evaluate the Fusion of Attribute-level and Instance-level Knowledge[J].Journal of Qingdao University(Natural Science Edition),2014(2):29-33,38. |
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| Authors: | ZHOU Yuan-ke SHAO Feng-jing WU Shun-yao |
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| Institution: | (a. College of Information Engineering, b. College of Qingdao University, Qingdao 26G071 Engineering, |
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| Abstract: | Not all the prior knowledge can improve clustering quality, so evaluating the merit of prior knowledge is extremely important for semi-supervised clustering. In recent years, some researchers haw~ proposed an effective measure to evaluate instance level knowledge in the form of pair-wise constraints, in formativeness and coherence. In this paper, we have further extended the work into the evaluation of altribute-level knowledge in the form of attribute order preferences. The proposed measure includes two as pects, informativeness and effectiveness, provided that instance-level knowledge in the form of pair wise constraints are also available. Experiments prove the effectiveness of the proposed method. |
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| Keywords: | semi-supervised clustering pair-wise constraints attribute order preferences |
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