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Robin Boswell

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4 papers
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4

IJCAI Conference 2011 Conference Paper

Finding the Hidden Gems: Recommending Untagged Music

  • Ben Horsburgh
  • Susan Craw
  • Stewart Massie
  • Robin Boswell

We have developed a novel hybrid representation for Music Information Retrieval. Our representation is built by incorporating audio content into the tag space in a tag-track matrix, and then learning hybrid concepts using latent semantic analysis. We apply this representation to the task of music recommendation, using similarity-based retrieval from a query music track. We also develop a new approach to evaluating music recommender systems, which is based upon the relationship of users liking tracks. We are interested in measuring the recommendation quality, and the rate at which cold-start tracks are recommended. Our hybrid representation is able to outperform a tag-only representation, in terms of both recommendation quality and the rate that cold-start tracks are included as recommendations.

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KER Journal 2000 Journal Article

Validation and verification of knowledge-based systems: report on EUROVAV99

  • Frans Coenen
  • Trevor Bench-Capon
  • Robin Boswell
  • JULIETTE DIBIE-BARTHÉLEMY
  • BARRY EAGLESTONE
  • RIK GERRITS
  • Eric Grégoire
  • ANTONI LIGE¸ZA

Knowledge-Based (KB) technology is being applied to complex problem solving and safety and business critical tasks in many application domains. Concerns have naturally arisen as to the dependability of Knowledge-Based Systems (KBS). As with any software, attention to quality and safety must be paid throughout development of a KBS, and rigorous Verification and Validation (V&V) techniques must be employed. Research in V&V of KBSs has emerged as a distinct field only in the last decade, and is intended to address issues associated with quality and safety aspects of KBSs, and to provide such applications with the same degree of dependability as conventional applications. In recent years, V&V of KBSs has been the topic of annual workshops associated with the main AI conferences, such as AAAI, IJCAI and ECAI.

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AAAI Conference 1999 Conference Paper

Representing Problem-Solving for Knowledge Refinement

  • Susan Craw
  • Robin Boswell
  • The Robert Gordon University

Knowledge refinementtools seek to correct faulty knowledgebased systems (KBSs)by identifying and repairing potentially faulty rules. Thegoal of the KRuSTWorks project is to provide a source of refinement componentsfrom whichspecialised refinementtools tailored to the needs of a range of KBSs are built. A core refinement algorithm reasons about the knowledgethat has been applied, but this approach demands general knowledge structures to represent the reasoning of a particular problemsolving episode. This paper investigates somecomplex formsof rule interaction and defines a knowledgestructure encompassing these. The approach has been applied to KBSs built in four shells andis demonstrated on a small examplethat incorporates someof the complexity foundin real applications.

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