Similarity score for information filtering thresholds in business processes

The tremendous growth in the amount of information available poses some key challenges for information filtering and retrieval. Users not only expect high quality and relevant information, but also wish that the information he presented in an as efficient way as possible. The traditional filtering methods, however, only consider the relevant values of document. These conventional methods fail to consider the efficiency of documents retrieval. In this paper, we propose a new algorithm to calculate an index called document similarity score based on elements of the document. Using the index, document profile is derived. Any documents with the similarity score above a given threshold is clustered. Using these pre-clustered documents, information filtering and retrieval can be made more efficient. Experimental results clearly show our proposed method tremendously improves the efficiency of information filtering and retrieval. We also give an example application of our proposed method in business processes.