Supporting Efficient Top-k Queries in Type-Ahead
Author : lindy-dunigan | Published Date : 2025-05-10
Description: Supporting Efficient Topk Queries in TypeAhead Search Guoliang Li1 Jiannan Wang1 Chen Li2 Jianhua Feng1 1 Tsinghua University 2 UC Irvine Bimaple Technology Inc SIGIR 2012 Portland Oregon Query suggestions Li Wang Li and Feng
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Transcript:Supporting Efficient Top-k Queries in Type-Ahead:
Supporting Efficient Top-k Queries in Type-Ahead Search Guoliang Li1, Jiannan Wang1, Chen Li2, Jianhua Feng1 1 Tsinghua University 2 UC Irvine, Bimaple Technology Inc. SIGIR 2012, Portland, Oregon Query suggestions Li, Wang, Li, and Feng Tsinghua/UC Irvine/Bimaple 2 Type-ahead search (instant search) Li, Wang, Li, and Feng 3 Finding answers instantly! Tsinghua/UC Irvine/Bimaple ipubmed.ics.uci.edu Li, Wang, Li, and Feng Tsinghua/UC Irvine/Bimaple 4 Advantages of instant fuzzy search Li, Wang, Li, and Feng Tsinghua/UC Irvine/Bimaple 5 Save time Challenges Speed “100ms rule” Prefix matching Fuzzy matching Li, Wang, Li, and Feng Tsinghua/UC Irvine/Bimaple 6 Techniques for computing top-k answers in instant fuzzy search without generating all candidates Li, Wang, Li, and Feng Tsinghua/UC Irvine/Bimaple 7 Contributions Ranking framework Index Structures Algorithms Experimental evaluation Outline Problem Formulation Instant exact search Instant fuzzy search Experiments Li, Wang, Li, and Feng Tsinghua/UC Irvine/Bimaple 8 Problem Formulation Data: records Query: w1, w2, …, wm wm partial keyword Answers: k best records Li, Wang, Li, and Feng Tsinghua/UC Irvine/Bimaple 9 graph icde li Prefix Aggregate Ranking Framework Li, Wang, Li, and Feng Tsinghua/UC Irvine/Bimaple 10 graph, gray, gross, icde, lin, liu Record Query graph icde li Score(graph) Score(icde) Score(lin) Score(liu) Max Trie Index structures g r a i l c d e m o p y h s u p s i u i n u Li, Wang, Li, and Feng Tsinghua/UC Irvine/Bimaple 11 Inverted Index {graph, icde, li} k=1 Basic Solution g r a i l c d e m o p y h s u p s i u i n u graph icde lin liu Li, Wang, Li, and Feng Tsinghua/UC Irvine/Bimaple 12 Optimization 1: Heap-based Method Aggregate Max Heap graph icde lin liu GetMax() Li, Wang, Li, and Feng Tsinghua/UC Irvine/Bimaple 13 Optimization 2: Top-k List-Merging Algorithm Example: Threshold algorithm Li, Wang, Li, and Feng Tsinghua/UC Irvine/Bimaple 14 Efficient Random Access: How? g r a i l c d e m o p y h s u p s i u i n u Li, Wang, Li, and Feng Tsinghua/UC Irvine/Bimaple 15 Forward index [Ji et al. WWW’09] Keyword ID Weight Li, Wang, Li, and Feng Tsinghua/UC Irvine/Bimaple 16 g r a i l c d e m o p y h s u p s i u i n u 1 2 3 4 5 6 7 8 9 [1, 1] [1, 2] [3,3] [4, 4] [3, 4] [1, 4] [1,
