Presentation is loading. Please wait.

Presentation is loading. Please wait.

Efficient Interactive Fuzzy Keyword Search Shengyue Ji 1, Guoliang Li 2, Chen Li 1, Jianhua Feng 2 1 University of California, Irvine 2 Tsinghua University.

Published byJamison Gadsden Modified over 9 years ago

Similar presentations

Presentation on theme: "Efficient Interactive Fuzzy Keyword Search Shengyue Ji 1, Guoliang Li 2, Chen Li 1, Jianhua Feng 2 1 University of California, Irvine 2 Tsinghua University."— Presentation transcript:

1 Efficient Interactive Fuzzy Keyword Search Shengyue Ji 1, Guoliang Li 2, Chen Li 1, Jianhua Feng 2 1 University of California, Irvine 2 Tsinghua University

2 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Too many results! Traditional Keyword Search No result! Complicated and still no result!

3 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Interactive Fuzzy Keyword Search Features:  Interactive: data exploration  Fuzzy: error tolerant  Multiple keywords: search on-the- fly

4 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Fundamentals  Data  R: a set of records  W: a set of distinct words  Query  Q = {p 1, p 2, …, p l }: a set of prefixes  δ: Edit-distance threshold  Query result  R Q : a set of records such that each record has all query prefixes or their similar forms (conjunctive)

5 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Contributions / Outline  Step 1  Incremental fuzzy prefix matching  Step 2  Multi-prefix intersection methods  Cache-based prefix intersection

6 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Observation  W = {exam, example, exemplar, exempt, sample}  δ = 2 PrefixDistance exam2 examp1 exampl0 example1 exemp2 exempt2 exempl1 exempla2 sampl2 PrefixDistance examp2 exampl1 example0 exempl2 exempla2 sample2 delete e match e delete e substitute e with a match e Q’ = examplQ = example

7 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Trie Indexing Computing set of active nodes Φ Q  Initialization  Incremental step e x a m p l $ $ e m p l a r $ t $ s a m p l e $ PrefixDistance examp2 exampl1 example0 exempl2 exempla2 sample2 Active nodes for Q = example e 2 1 0 2 2 2

8 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Initialization  Q = ε e x a m p l $ $ e m p l a r $ t $ s a m p l e $ PrefixDistance 0 11 22 PrefixDistance 0 e1 ex2 s1 sa2 PrefixDistance ε 0 Initializing Φ ε with all nodes within in depth of δ e

9 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Incremental Computation: Algorithm  Incremental computation from Φ Q’ to Φ Q  add( Φ Q, ) has effect only if there exists no active node in Φ Q with the same n and smaller d FOR EACH FROM Φ Q’ Deletion add( Φ Q, ) SubstitutionFOR EACH n’ FROM non-matching children of n add( Φ Q, ) Match add( Φ Q, ) (m is the matching child of n) InsertionFOR EACH m’ FROM descendents of m add( Φ Q, ) (x is the distance from m’ to m) Algorithm Details

10 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng e Incremental Computation: Example  Q = e e x a m p l $ $ e m p l a r $ t $ s a m p l e $ PrefixDistance ε 0 e1 ex2 s1 sa2 Prefix# OpBaseOp ε 1 ε del e s1 ε sub e/s e0 ε mat e ex1 ε ins x exa2 ε Ins xa exe2 ε Ins xe Prefix# OpBaseOpPrefix# OpBaseOp ε 1 ε del e Prefix# OpBaseOp ε 1 ε del e s1 ε sub e/s Prefix# OpBaseOp ε 1 ε del e s1 ε sub e/s e0 ε mat e 1 10 1 22 e2edel e ex2esub e/xex3 del e exa3exsub e/a exe2exmat e s2sdel e sa2ssub e/asa3 del e Active nodes for Q = ε Active nodes for Q = e 2

11 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Incremental Computation: Discussion  Insertions  Needed after matches  Not needed after deletions and substitutions deletions and insertions do not co-occur in adjacent positions adjacent substitutions and insertions are interchangeable  Correctness and Completeness  Can be proved by reducing from/to edit-distance computation

12 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Outline  Step 1  Incremental fuzzy prefix matching  Step 2  Multi-prefix intersection methods  Cache-based prefix intersection

13 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Multi-Prefix Intersection  Q = vldb li  Multi-prefix intersection  To return records such that each record has all query keywords as prefixes (or their similar forms) IDRecord 1Li data… 2data… 3data Lin… 4Lu Lin Luis… 5Liu… 6VLDB Lin data… 7VLDB… 8Li VLDB… 6VLDB Lin data… 8Li VLDB…

14 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Multi-Prefix Intersection: Method 1 IDRecord 1Li data… 2data… 3data Lin… 4Lu Lin Luis… 5Liu… 6VLDB Lin data… 7VLDB… 8Li VLDB… d a t a $ l i nu $ u $ v l d b $ 12361236 5 4 678678 $ 346346 i s $ 1818 $ 4 1 3 4 5 6 8 6 7 8 li vldb 6 8  Q = vldb li Space costInverted index Time costUnion + intersection

15 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Multi-Prefix Intersection: Method 2 Forward List 1 2 1 1 3 3 5 6 4 1 3 7 7 2 7 d a t a $ l i nu $ u $ v l d b $ 12361236 5 4 678678 $ 346346 i s $ 1818 $ 4 IDRecord 1Li data… 2data… 3data Lin… 4Lu Lin Luis… 5Liu… 6VLDB Lin data… 7VLDB… 8Li VLDB… [1, 7] [1, 1] [2, 6] [2, 4] 1 2 34 5 67 [3, 3][4, 4] [5, 6] [6, 6] [7, 7]  Q = vldb li 678678 [2, 4] Read eachVerify/Probe 6VLDB Lin data…1 3 7 8Li VLDB…2 7 Space costInverted + forward index Time costProbing forward lists

16 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Cache-Based Prefix Intersection  Example  Q 1 = cs co  Q 2 = cs conf  Q 3 = cs conf vanc  Simple Method  computing and caching the entire answers of Q 1  computing the answers of Q 2 from Q 1 incrementally  Problem  answers of Q1 may be very large and not completely used in the results displayed

17 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Cache-Based Prefix Intersection  Reducing cached answers  compute and cache only needed answers  for subsequent queries, compute the answers: from the cached answers from resuming previously terminated computation Q = cs co cached answers of cs co traversal list: inverted list of cs compute Q = cs conf Verify cached answers of cs conf Compute

18 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Additional Features  Ranking  Highlighting  Synonyms

19 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Experimental Results  Computing similar prefixes

20 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Experimental Results  Multi-prefix intersection

21 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Experimental Results  Overall scalability

22 Questions ? Thank You! Questions? UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng TASTIER: Efficient Auto-Completion, Type-Ahead Search http://tastier.ics.uci.edu/

23 UC Irvine & Tsinghua Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng Efficient Interactive Fuzzy Keyword Search Shengyue Ji, Guoliang Li, Chen Li, Jianhua Feng

Download ppt "Efficient Interactive Fuzzy Keyword Search Shengyue Ji 1, Guoliang Li 2, Chen Li 1, Jianhua Feng 2 1 University of California, Irvine 2 Tsinghua University."

Similar presentations

1 Efficient Processing of XML Twig Patterns with Parent Child Edges: A Look-ahead Approach Jiaheng Lu, Ting Chen, Tok Wang Ling National University of.

1 Efficient Processing of XML Twig Patterns with Parent Child Edges: A Look-ahead Approach Jiaheng Lu, Ting Chen, Tok Wang Ling National University of.
Space-Constrained Gram-Based Indexing for Efficient Approximate String Search, ICDE 2009, Shanghai Space-Constrained Gram-Based Indexing for Efficient.

Space-Constrained Gram-Based Indexing for Efficient Approximate String Search, ICDE 2009, Shanghai Space-Constrained Gram-Based Indexing for Efficient.
String Similarity Measures and Joins with Synonyms

String Similarity Measures and Joins with Synonyms
Optimal Top-k Generation of Attribute Combinations based on Ranked Lists Jiaheng Lu, Renmin University of China Joint work with Pierre Senellart, Chunbin.

Optimal Top-k Generation of Attribute Combinations based on Ranked Lists Jiaheng Lu, Renmin University of China Joint work with Pierre Senellart, Chunbin.
A Minimum Cost Path Search Algorithm Through Tile Obstacles Zhaoyun Xing and Russell Kao Sun Microsystems Laboratories.

A Minimum Cost Path Search Algorithm Through Tile Obstacles Zhaoyun Xing and Russell Kao Sun Microsystems Laboratories.
Extending Q-Grams to Estimate Selectivity of String Matching with Low Edit Distance [1] Pirooz Chubak May 22, 2008.

Extending Q-Grams to Estimate Selectivity of String Matching with Low Edit Distance [1] Pirooz Chubak May 22, 2008.
Efficient Top-k Search across Heterogeneous XML Data Sources Jianxin Li 1 Chengfei Liu 1 Jeffrey Xu Yu 2 Rui Zhou 1 1 Swinburne University of Technology.

Efficient Top-k Search across Heterogeneous XML Data Sources Jianxin Li 1 Chengfei Liu 1 Jeffrey Xu Yu 2 Rui Zhou 1 1 Swinburne University of Technology.
Computing Structural Similarity of Source XML Schemas against Domain XML Schema Jianxin Li 1 Chengfei Liu 1 Jeffrey Xu Yu 2 Jixue Liu 3 Guoren Wang 4 Chi.

Computing Structural Similarity of Source XML Schemas against Domain XML Schema Jianxin Li 1 Chengfei Liu 1 Jeffrey Xu Yu 2 Jixue Liu 3 Guoren Wang 4 Chi.
Indexing DNA Sequences Using q-Grams

Indexing DNA Sequences Using q-Grams
Jan SedmidubskyOctober 28, 2011Scalability and Robustness in a Self-organizing Retrieval System Jan Sedmidubsky Vlastislav Dohnal Pavel Zezula On Investigating.

Jan SedmidubskyOctober 28, 2011Scalability and Robustness in a Self-organizing Retrieval System Jan Sedmidubsky Vlastislav Dohnal Pavel Zezula On Investigating.
Efficient Approximate Search on String Collections Part I Marios Hadjieleftheriou Chen Li 1.

Efficient Approximate Search on String Collections Part I Marios Hadjieleftheriou Chen Li 1.
Chen Li ( 李晨 ) Chen Li Search As You Type Joint work with colleagues at UCI and Tsinghua.

Chen Li ( 李晨 ) Chen Li Search As You Type Joint work with colleagues at UCI and Tsinghua.
Chen Li ( 李晨 ) Chen Li Scalable Interactive Search NFIC August 14, 2010, San Jose, CA Joint work with colleagues at UC Irvine and Tsinghua University.

Chen Li ( 李晨 ) Chen Li Scalable Interactive Search NFIC August 14, 2010, San Jose, CA Joint work with colleagues at UC Irvine and Tsinghua University.
Jianxin Li, Chengfei Liu, Rui Zhou Swinburne University of Technology, Australia Wei Wang University of New South Wales, Australia Top-k Keyword Search.

Jianxin Li, Chengfei Liu, Rui Zhou Swinburne University of Technology, Australia Wei Wang University of New South Wales, Australia Top-k Keyword Search.
Modern information retrieval Modelling. Introduction IR systems usually adopt index terms to process queries IR systems usually adopt index terms to process.

Modern information retrieval Modelling. Introduction IR systems usually adopt index terms to process queries IR systems usually adopt index terms to process.
Efficient Keyword Search for Smallest LCAs in XML Database Yu Xu Department of Computer Science & Engineering University of California, San Diego Yannis.

Efficient Keyword Search for Smallest LCAs in XML Database Yu Xu Department of Computer Science & Engineering University of California, San Diego Yannis.
Supporting top-k join queries in relational databases Ihab F. Ilyas, Walid G. Aref, Ahmed K. Elmagarmid Presented by Rebecca M. Atchley Thursday, April.

Supporting top-k join queries in relational databases Ihab F. Ilyas, Walid G. Aref, Ahmed K. Elmagarmid Presented by Rebecca M. Atchley Thursday, April.
Effective Keyword Based Selection of Relational Databases Bei Yu, Guoliang Li, Karen Sollins, Anthony K.H Tung.

Effective Keyword Based Selection of Relational Databases Bei Yu, Guoliang Li, Karen Sollins, Anthony K.H Tung.
Nearest Neighbor Queries using R-trees

Nearest Neighbor Queries using R-trees
Dong Deng, Guoliang Li, Jianhua Feng Database Group, Tsinghua University Present by Dong Deng A Pivotal Prefix Based Filtering Algorithm for String Similarity.

Dong Deng, Guoliang Li, Jianhua Feng Database Group, Tsinghua University Present by Dong Deng A Pivotal Prefix Based Filtering Algorithm for String Similarity.

Similar presentations

Ads by Google