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Topic Hierarchy Construction for the Organization of Multi-Source User Generated Contents Date : 2013/09/17 Source : SIGIR’13 Authors : Zhu, Xingwei Ming Zhao-Yan Zhu, Xiaoyan Chua, Tat-Seng Advisor : Dr.Jia-ling, Koh Speaker : Wei, Chang 1
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Topic Hierarchy Construction for the Organization of Multi-Source User Generated Contents

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Topic Hierarchy Construction for the Organization of Multi-Source User Generated Contents. Date : 2013/09/17 Source : SIGIR’13 Authors : Zhu, Xingwei Ming Zhao-Yan Zhu, Xiaoyan Chua, Tat- Seng Advisor : Dr.Jia -ling, Koh Speaker : Wei, Chang. Outline. Introduction Approach - PowerPoint PPT Presentation
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Page 1: Topic Hierarchy Construction for the Organization of Multi-Source User Generated  Contents

Topic Hierarchy Construction for the Organization of Multi-Source User Generated Contents

Date : 2013/09/17Source : SIGIR’13Authors : Zhu, Xingwei

Ming Zhao-YanZhu, XiaoyanChua, Tat-Seng

Advisor : Dr.Jia-ling, KohSpeaker : Wei, Chang

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Outline

• Introduction• Approach• Experiment• Conclusion

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IPhone 5s? IPhone 5c?

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Multi-Source User Generated Contents

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Problem Formulation

• Goal : Given a root topic C and its information source set Sc, we aim to build and continuously update a topic hierarchy H for C in order to organize the information in Sc according to their relevant topics.

• In this paper, Sc={Blogger, Twitter, community QA site(cQA)}

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Outline

• Introduction• Approach• Framework• Topic Term Identification• Topic Relation Identification• Topic Hierarchy Generation• Topic Hierarchy Update

• Experiment• Conclusion 6

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Framwork

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Topic Term Identification

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User Generated Contents

Potential Grounding

Topics

Grounding Topic Set

Heuristic Rules

TF-IDFFinal

Candidate Topic SetExternal

Sources

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Heuristic Rules

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Grounding Topic Set

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Apple Inc.

T-Mobile

IPhone

IOS

Price

64-bit

Smartphone

Blog 1

Tweet 2

QA 1

QA 2

Tweet 1

TFIDF

IPhoneApple Inc.

T-MobileApple Inc.

IOSApple Inc.

IOS

IPhone

AppleIOS

IPhone

Page 11: Topic Hierarchy Construction for the Organization of Multi-Source User Generated  Contents

Grounding Topic Set

• Blogs • Use the content and title• Double weights of terms in titles• Use the top 5 terms

• cQAs :• Use the question title, description and the best

answers• Use the top 5 terms

• Tweets :• Use the content• Use the top 1 terms

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Page 12: Topic Hierarchy Construction for the Organization of Multi-Source User Generated  Contents

Topic Set Extension

• What we already have :• Grounding topic set

• What it lacks :• Middle level topic

• How to get middle level topics :• Search Engine : 2 patterns• * such as <slot>• <slot> of *

• WordNet : direct hypernym• Wikipedia : category tags

• Final candidate topic set : 12

Page 13: Topic Hierarchy Construction for the Organization of Multi-Source User Generated  Contents

Outline

• Introduction• Approach• Framework• Topic Term Identification• Topic Relation Identification• Topic Hierarchy Generation• Topic Hierarchy Update

• Experiment• Conclusion 13

Page 14: Topic Hierarchy Construction for the Organization of Multi-Source User Generated  Contents

Topic Relation Identification

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IPhone IPhone 5s

Apple Inc.

𝑒(𝑟 (𝑡𝐴 , 𝑡𝐵)) 𝑒(𝑟 (𝑡𝐵 ,𝑡 𝐴))

𝑒(𝑟 (𝑡𝐶 ,𝑡𝐵))

𝑒(𝑟 (𝑡𝐴 , 𝑡𝐶 )) 𝑒(𝑟 (𝑡𝐶 ,𝑡 𝐴))

𝑒(𝑟 (𝑡𝐵 ,𝑡𝐶))Denote as a sub-topic relation, which means is a sub-topic of

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Topic Relation Identification

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Page 16: Topic Hierarchy Construction for the Organization of Multi-Source User Generated  Contents

Evidences from the Information Source Set• , : the cosine similarity between the corresponding contexts

of them• V=(smart phone, price, buy, iOS, Android)

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Page 17: Topic Hierarchy Construction for the Organization of Multi-Source User Generated  Contents

Evidences from Wikipedia

Pointwise Mutual Information (PMI)

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Evidences from WordNet

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Evidences from Search Engine Results• Pattern-based evidences• Query = “tA such as tB and” root topic• = 1 if the search engine returns more than ζ results that

contain this query; otherwise it is set to 0.

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Combine Evidences

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Outline

• Introduction• Approach• Framework• Topic Term Identification• Topic Relation Identification• Topic Hierarchy Generation• Topic Hierarchy Update

• Experiment• Conclusion 21

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Topic Hierarchy Generation

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Topic Hierarchy Generation

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Topic Hierarchy Generation

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Topic Hierarchy Generation

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Edge Weighting

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Hierarchy Pruning• Use the Chu- Liu/Edmond’s optimum branching algorithm• every non-root node has only one parent and the sum of the

edge weights are maximized• remove • (1) the nodes that are not reachable for the root topic and • (2) the leaf nodes that are not in the grounding topic set.

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Topic Hierarchy Update

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Page 29: Topic Hierarchy Construction for the Organization of Multi-Source User Generated  Contents

Outline

• Introduction• Approach• Framework• Topic Term Identification• Topic Relation Identification• Topic Hierarchy Generation• Topic Hierarchy Update

• Experiment• Conclusion 29

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Topic Term Identification

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Topic Hierarchy Generation

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Topic Hierarchy Generation

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Hierarchy Update

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Page 34: Topic Hierarchy Construction for the Organization of Multi-Source User Generated  Contents

Outline

• Introduction• Approach• Framework• Topic Term Identification• Topic Relation Identification• Topic Hierarchy Generation• Topic Hierarchy Update

• Experiment• Conclusion 34

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Conclusion

• Given a root topic, we used evidences from multiple UGCs to identify topic terms and sub-topic relations between them. With these topic terms, a graph-based algorithm was applied to generate and update the topic hierarchies, on which the UGCs can be organized according to their relevant topics.

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