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A Fuzzy Similarity Measure for Search Results Evaluation

机译:用于搜索结果评估的模糊相似度量

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The wide spread of the world wide web, the accelerating internet technologies development and the continuous upload of documents has produced large volumes of data. As a result, a huge amount of similar information is available on the web however very difficult to retrieve the best, concise and most precise one. In addition, the continuous upload of information leads to another issue which is documents' redundancy. It still an issue that irritates researchers due to the multiplicity of duplicated documents. Hence, the unsatisfaction of the user is due to the irrelevance and the multiple duplications in the search results. Therefore, the need to study the fields of information retrieval and document similarity is essential to ameliorate the results. Working on retrieving and comparing information, then deleting duplications will finally achieve the needed results in short time and efficient way. For this reason, we propose, in this paper, a new approach which detects and deletes automatically duplicated research results. This approach is based on fuzzy logic and distance measurements. In fact, it has shown promising results.
机译:万维网广泛传播,加速互联网技术开发和连续上传文档已经产生了大量的数据。因此,网络上可获得大量类似的信息,但是非常难以检索最佳,简洁,最精确的信息。此外,持续上传信息导致另一个是文件的冗余。由于多重复制文档,它仍然是一个刺激研究人员的问题。因此,用户不满意是由于搜索结果中的无关紧要和多重重复。因此,需要研究信息检索和文档相似性的领域对于改善结果至关重要。正在研究检索和比较信息,然后删除重复将最终以短时间和有效的方式实现所需的结果。出于这个原因,我们提出了一种新方法,它检测和删除自动重复的研究结果。这种方法基于模糊逻辑和距离测量。事实上,它表明了有希望的结果。

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