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Exploring Structured Documents and Query Formulation Techniques for Patent Retrieval

机译:探索专利检索的结构化文档和查询制定技术

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This paper presents the experiments and results of DCU in CLEF-IP 2009. Our work applied standard information retrieval (IR) techniques to patent search. Different experiments tested various methods for the patent retrieval, including query formulation, structured index, weighted fields, document filtering, and blind relevance feedback. Some methods did not show expected good retrieval effectiveness such as blind relevance feedback, other experiments showed acceptable performance. Query formulation was the key to achieving better retrieval effectiveness, and this was performed through assigning higher weights to certain document fields. Further experiments showed that for longer queries, better results are achieved but at the expense of additional computations. For the best runs, the retrieval effectiveness is still lower than for IR applications for other domains, illustrating the difficulty of patent search. The official results have shown that among fifteen participants we achieved the seventh and the fourth ranks from the mean average precision (MAP) and recall point of view, respectively.
机译:本文介绍了CLEF-IP 2009中DCU的实验和结果。我们的工作将标准信息检索(IR)技术应用于专利检索。不同的实验测试了专利检索的各种方法,包括查询表述,结构化索引,加权字段,文档过滤和盲目的相关性反馈。一些方法没有显示出预期的良好检索效果,例如盲目相关反馈,而其他实验则显示了​​可接受的性能。查询公式化是实现更好的检索效率的关键,这是通过为某些文档字段分配更高的权重来实现的。进一步的实验表明,对于更长的查询,可以获得更好的结果,但是要付出额外的计算代价。对于最佳运行,检索效率仍然低于其他领域的IR应用程序,这说明了专利检索的难度。官方结果表明,在15名参与者中,我们从平均平均精度(MAP)和召回率的角度来看分别获得了第七和第四名。

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