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Key Blog Distillation: Ranking Aggregates

Presenter : Yu-hui Huang

Authors :Craig Macdonald,

Iadh Ounis

CIKM 2009

國立雲林科技大學National Yunlin University of Science and Technology

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Intelligent Database Systems Lab

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I. M.Outline

Motivation Objective Methodology Experiments Conclusion Comments

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I. M.Motivation Help user to look for blogs that interest them. What is importance degree for each search result .

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I. M.Objective To provide key blogs relevant to the query topic area. Ranking the blog according to degree of importance. Blog distillation ： could be add search feet to directories or

return suggest for his/her RSS.

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I. M.Methodology Ranking ：

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I. M.Methodology Ranking ：

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I. M.Methodology Weight function

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qtw ： don’t ask me

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I. M.Methodology Three hypotheses: to model more fully the definition of a relevant blog

given to the assessors. Central Interest:

If the posts of each blog are clustered, then relevant blogs will have blog posts about the topic in one of the larger clusters.

Recurring Interest: Relevant blogs will cover the topic many times across the timespan of the collection.

Focused Interest: Relevant blogs will mainly blog around a central topic area - i.e. they will have a coherent language model with which they blog.

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I. M.Methodology Central interest ： (quality score)

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cluster(p;B) is the rank of the cluster in which post p occurred for blog B (largest cluster has rank 1).

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I. M.Methodology Recurring interest ：

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I. M.Methodology Focused interest ：

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I. M.Experiments

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I. M.Methodology Mean Average Precision (MAP)

Mean Reciprocal Rank(MRR)

P @ rank 10 ：precision @ rank 10 direct translated into Chinese please

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I. M.Experiments

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I. M.Conclusion

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Add normalization component to the voting techniques that could indeed improve the retrieval performance.

Authors consider that using the XML content will reduce the amount of noise. (god)

Intelligent Database Systems Lab

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I. M.Comments

Advantage …

Drawback This paper is non detail Can description for example

Application Search engine (maybe)

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