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Key Blog Distillation: Ranking Aggregates

Key Blog Distillation: Ranking Aggregates. Presenter : Yu-hui Huang Authors :Craig Macdonald, Iadh Ounis. 國立雲林科技大學 National Yunlin University of Science and Technology. CIKM 2009. Outline. Motivation Objective Methodology Experiments Conclusion Comments.

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Key Blog Distillation: Ranking Aggregates

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  1. Key Blog Distillation: Ranking Aggregates Presenter : Yu-hui Huang Authors :Craig Macdonald, Iadh Ounis 國立雲林科技大學 National Yunlin University of Science and Technology CIKM 2009

  2. Outline • Motivation • Objective • Methodology • Experiments • Conclusion • Comments

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

  4. 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.

  5. Methodology • Ranking：

  6. Methodology • Ranking：

  7. Methodology • Weight function • qtw：don’t ask me 

  8. 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.

  9. Methodology • Central interest： (quality score) • cluster(p;B) is the rank of the cluster in which post p occurred for blog B (largest cluster has rank 1).

  10. Methodology • Recurring interest：

  11. Methodology • Focused interest：

  12. Experiments

  13. Methodology • Mean Average Precision (MAP) • Mean Reciprocal Rank(MRR) • P @ rank 10： precision @ rank 10 direct translated into Chinese please

  14. Experiments

  15. Conclusion • 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) 15

  16. Comments • Advantage • … • Drawback • This paper is non detail • Can description for example • Application • Search engine (maybe)

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