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Data mining for Web Video Auto Tagging TRAN Hoang Tung.

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Presentation on theme: "Data mining for Web Video Auto Tagging TRAN Hoang Tung."— Presentation transcript:

1 Data mining for Web Video Auto Tagging TRAN Hoang Tung

2 Outline Data mining for Web Video Auto Tagging Introducing myself General Context Explain what I want to do in my PhD thesis Data mining Applying data mining techniques into video tagging Last year and future plan! USTH Consortium - Toulouse /19/112

3 About myself My name is TRAN Hoang Tung Arrival date: 25 th Oct 2010 Im working in Hubert Curien Laboratory, Jean Monnet University and CNRS City: Saint Etienne (close to Lyon and Grenoble) My supervisors: Francois Jacquenet (full professor) Elisa Fromont (assistant professor) Baptiste Jeudy (assistant professor) Keywords: data mining, video tagging, video annotation USTH Consortium - Toulouse /19/113

4 USTH Consortium - Toulouse /19/114

5 Web videos (Youtube…) Current video search engines are text-based (title, description, tags). Title & description are written by each uploader (normally as a complete phase). Tags are single words!! However, tags are notoriously: Incomplete (dont fully represent such video) Incorrect (spam, increase number of view) Unranked (the most important tag is not the first tag) My thesis goal: creating an auto-tagging system which reduces above disadvantages of current tags. USTH Consortium - Toulouse /19/115

6 Data mining Data mining is a field of computer science, and more precisely of artificial intelligence. The goal is to describe (very) large data in an informative way. For example discovering patterns ! Example: Market-Basket Analysis USTH Consortium - Toulouse /19/116 TIDitems 1 {bread, milk} 2 {bread, diaper, beers, eggs} 3 {bread, diaper, beers, cola} 4 {bread, diaper, beers, milk} 5 {bread, diaper, cola, milk} Consider item set {bread, diaper}: Support = 4/5 = 80% Consider association rule: {bread, diaper} -> beers with confidence: = s({bread,diaper,beers})/s({bread,diaper}) =3/4

7 Data mining & video tagging Assumption: similar videos will have (with high probability) similar tags. Steps: Compute similarities between videos based on patterns Propagate the tags USTH Consortium - Toulouse /19/117

8 The Past and Future! Last year: Studying data mining Followed a master course in Machine Learning Participating to a winter school in Machine Learning applied to image processing Reading bibliography about data mining applied to video analysis Studying French ! (240 hours) Next year: Take a look at other types of patterns : discriminative patterns, sequences, … Try other techniques to convert video into binary form Write something ! Write something ! USTH Consortium - Toulouse /19/118

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