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Anti-spam Algorithm TrustRank 、 Hilltop 954203041 林裕得 954203057 蔡繼正
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Introduction(1/3) ,[object Object],[object Object],[object Object],0.4 0.4 0.2
Introduction(2/3) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Introduction(3/3) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Compare with Page Rank 、 Trust Rank 、 Hilltop(1/3) ,[object Object]
Compare with Page Rank 、 Trust Rank 、 Hilltop(2/3) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Compare with Page Rank 、 Trust Rank 、 Hilltop(3/3) 0.16 0.16 0.16 0.16 0.16 0.16 0.33 0 0.33 0 0.33 0 0.5 0.2 0.3 Algorithm 1 or 0 Average Initial Score Expert pages All pages All pages Inlinks Source Hilltop Trust Rank Page Rank  
Trust Rank(1/7) ,[object Object],[object Object],[object Object],[object Object],[object Object],0  0.5  0  … 0  0  0.5 … 0  0.5  0  … ………………
 
Trust Rank (2/7) ,[object Object],[object Object]
U S M 1 N …………… . M
Trust Rank(3/7) ,[object Object]
Trust Rank(4/7) ,[object Object],ex, L=3, seed set is {2,4,5}
Trust Rank(5/7) ,[object Object],[object Object]
Trust Rank(6/7) ,[object Object],T d t* …………… . M
Trust Rank(7/7) ,[object Object]
Hilltop (1/9) ,[object Object],[object Object],[object Object],[object Object]
Hilltop (2/9) ,[object Object],[object Object],[object Object],[object Object],non-affiliated pages expert page …… Index key phrases
Hilltop (3/9) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Hilltop (4/9) ,[object Object],[object Object],non-affiliated pages expert page ……
Hilltop (5/9) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Hilltop (6/9) ,[object Object],[object Object],[object Object],[object Object],<title>  中央大學  </title> <h1>  資管系  </h1> <A> 001 </A> <A> 002 </A> <h1>  企管系  </h1> <A> 001 </A> <A> 002 </A>
Hilltop (7/9) ,[object Object],[object Object],[object Object],Target page  expert pages N = 200 …… Least 2 experts point to target
Hilltop (8/9) ,[object Object],[object Object]
Computing the Expert Score(1/2) S 0 :包含 k 個 ( 所有 )keywords 的 Key Phrase 的總值 S 1 :包含 k-1 個 keywords 的 Key Phrase 的總值 S 2 :包含 k-2 個 keywords 的 Key Phrase 的總值 S i  = SUM (key phrases p with k-i query terms)  LevelScore(p) * FullnessFactor(p,q) LevelScore : 16 of title, 6 of heading, 1 of anchor m is the number of terms in p which are not in q If m <= 2, FullnessFactor(p,q) = 1 If m > 2, FullnessFactor(p,q) = 1 – (m-2) / plen  Query: A B S 0  = 16*1 S 1  = 16*1 + 6*1 + 16*1 S 2  = 0 Title: A B C H1: A
Computing the Expert Score(2/2) S 0 :包含 k 個 ( 所有 )keywords 的 Key Phrase 的總值 S 1 :包含 k-1 個 keywords 的 Key Phrase 的總值 S 2 :包含 k-2 個 keywords 的 Key Phrase 的總值 Expert_Score  = ( 2 32  * S 0  ) + ( 2 16  * S 1  ) + S 2
Hilltop(9/9) ,[object Object],[object Object],[object Object]
Computing the Target Score(1/2) occ(w,T)  is the number of distinct key phrases in E that contain w and qualify the edge(E,T) If occ(w,T) is 0  for any query keyword  then the  Edge_Score(E,T) = 0 Otherwise, Edge_Score(E,T)  = Expert_Score(E) *  SUM (query keywords w)  occ(w,T) T E edge
Computing the Target Score(2/2) Target_Score  = SUM ( non-affiliated E)   Edge_Score(E,T) T E 1 E 2 E 3 E2 and E3 are affiliated,  and ES(E 2 ,T) > ES(E 3 ,T)
Evaluation-Trust Rank(1/3)
Evaluation-Trust Rank(2/3) ,[object Object]
Evaluation-Trust Rank(3/3) ,[object Object],[object Object]
Evaluation-Hilltop(1/2) ,[object Object]
Evaluation-Hilltop(2/2) ,[object Object]
Reference ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Q&A

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Anti Spam Algorithm

  • 1. Anti-spam Algorithm TrustRank 、 Hilltop 954203041 林裕得 954203057 蔡繼正
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  • 8. Compare with Page Rank 、 Trust Rank 、 Hilltop(3/3) 0.16 0.16 0.16 0.16 0.16 0.16 0.33 0 0.33 0 0.33 0 0.5 0.2 0.3 Algorithm 1 or 0 Average Initial Score Expert pages All pages All pages Inlinks Source Hilltop Trust Rank Page Rank  
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  • 12. U S M 1 N …………… . M
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  • 26. Computing the Expert Score(1/2) S 0 :包含 k 個 ( 所有 )keywords 的 Key Phrase 的總值 S 1 :包含 k-1 個 keywords 的 Key Phrase 的總值 S 2 :包含 k-2 個 keywords 的 Key Phrase 的總值 S i = SUM (key phrases p with k-i query terms) LevelScore(p) * FullnessFactor(p,q) LevelScore : 16 of title, 6 of heading, 1 of anchor m is the number of terms in p which are not in q If m <= 2, FullnessFactor(p,q) = 1 If m > 2, FullnessFactor(p,q) = 1 – (m-2) / plen Query: A B S 0 = 16*1 S 1 = 16*1 + 6*1 + 16*1 S 2 = 0 Title: A B C H1: A
  • 27. Computing the Expert Score(2/2) S 0 :包含 k 個 ( 所有 )keywords 的 Key Phrase 的總值 S 1 :包含 k-1 個 keywords 的 Key Phrase 的總值 S 2 :包含 k-2 個 keywords 的 Key Phrase 的總值 Expert_Score = ( 2 32 * S 0 ) + ( 2 16 * S 1 ) + S 2
  • 28.
  • 29. Computing the Target Score(1/2) occ(w,T) is the number of distinct key phrases in E that contain w and qualify the edge(E,T) If occ(w,T) is 0 for any query keyword then the Edge_Score(E,T) = 0 Otherwise, Edge_Score(E,T) = Expert_Score(E) * SUM (query keywords w) occ(w,T) T E edge
  • 30. Computing the Target Score(2/2) Target_Score = SUM ( non-affiliated E) Edge_Score(E,T) T E 1 E 2 E 3 E2 and E3 are affiliated, and ES(E 2 ,T) > ES(E 3 ,T)
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  • 37. Q&A