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On scalability of active learning for formulating query concepts

Published: 13 June 2004 Publication History

Abstract

Query-by-example and query-by-keyword both suffer from the problem of "aliasing," meaning that example-images and keywords potentially have variable interpretations or multiple semantics. For discerning which semantic is appropriate for a given query, we have established that combining active learning with kernel methods is a very effective approach. In this work, we first examine active-learning strategies, and then focus on addressing the challenges of two scalability issues: scalability in dataset size and in concept complexity. We present remedies, explain limitations, and discuss future directions that research might take.

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cover image ACM Conferences
CVDB '04: Proceedings of the 1st international workshop on Computer vision meets databases
June 2004
78 pages
ISBN:1581139179
DOI:10.1145/1039470
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 June 2004

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Author Tags

  1. active learning
  2. image retrieval
  3. query concept
  4. relevance feedback
  5. support vector machines

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  • (2014)Supervised Learning using an Active StrategyProcedia Technology10.1016/j.protcy.2013.12.47812(220-228)Online publication date: 2014
  • (2011)Query Concept LearningFoundations of Large-Scale Multimedia Information Management and Retrieval10.1007/978-3-642-20429-6_3(37-72)Online publication date: 26-Aug-2011
  • (2006)Support vector machine active learning for music retrievalMultimedia Systems10.1007/s00530-006-0032-212:1(3-13)Online publication date: 1-Aug-2006
  • (2005)Report from the first international workshop on computer vision meets databases (CVDB 2004)ACM SIGMOD Record10.1145/1058150.105816334:1(57-60)Online publication date: 1-Mar-2005
  • (2004)Multimodal concept-dependent active learning for image retrievalProceedings of the 12th annual ACM international conference on Multimedia10.1145/1027527.1027664(564-571)Online publication date: 10-Oct-2004

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