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Towards efficient top-k fuzzy auto-completion queries
- Source :
- Alexandria Engineering Journal. 61:5783-5791
- Publication Year :
- 2022
- Publisher :
- Elsevier BV, 2022.
-
Abstract
- Finding relevant objects in a large repository is a fundamental research problem occurring in many applications, such as: data cleaning, data integration, web search, and information retrieval. Instant type-ahead fuzzy search, where user types her query character by character and find the top-k relevant objects, has become widely involved in many applications because it provides the users with rapid response results and improves the user’s experience. The state-of-the-art algorithms are generally inefficient due to their breadth first search algorithm that results in repeated computations. To this end, we propose a novel depth-oriented instant type-ahead fuzzy search algorithm, that largely avoids repeated computations. The efficiency and effectiveness of the proposed approach are empirically demonstrated using real-world datasets. Experimental results show that our approach is 5–10 times faster than state-of-the-art approaches.
- Subjects :
- Computer science
020209 energy
Computation
Breadth-first search
General Engineering
02 engineering and technology
Approximate string matching
computer.software_genre
01 natural sciences
Fuzzy logic
010305 fluids & plasmas
Character (mathematics)
0103 physical sciences
0202 electrical engineering, electronic engineering, information engineering
Data mining
computer
Rapid response
Data integration
Instant
Subjects
Details
- ISSN :
- 11100168
- Volume :
- 61
- Database :
- OpenAIRE
- Journal :
- Alexandria Engineering Journal
- Accession number :
- edsair.doi...........e5cb4405c5d1c03f8addc9d9761f8655