Abstract
In modern information retrieval (IR) systems, scoring functions have been extensively adopted for sorting results. For a given document, the rank in sorted result lists with respect to hot searches can be considered as its influence. When a new document comes, can we use such IR systems to evaluate its influence before we insert it into the corpus? Such issue may not be solved very well by current IR systems with inverted indexes. In this paper, an influence measure based on documents’ global rank is proposed, and the inverted index structure has been extended by adding the position milestones for speeding up the ranking calculation. Moreover, a performance study using both real data and synthetic data verifies the effectiveness and the efficiency of our method.
The research of Yi Han was supported in part by by China National High-tech R&D Program (863 Program) under Grant No. 2007AA010502 and National Natural Science Foundation of China under Grant No. 60873204 and 60933005. All opinions, findings, conclusions and recommendations in this paper are those of the authors and do not necessarily reflect the views of the funding agencies.
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Wang, Y., Han, Y., Lu, T. (2010). Estimating the Influence of Documents in IR Systems: A Marked Indexing Approach. In: Taniar, D., Gervasi, O., Murgante, B., Pardede, E., Apduhan, B.O. (eds) Computational Science and Its Applications – ICCSA 2010. ICCSA 2010. Lecture Notes in Computer Science, vol 6019. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12189-0_23
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DOI: https://doi.org/10.1007/978-3-642-12189-0_23
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