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Final year IEEE projects 2016 based on Java Data Mining
  • Final year IEEE projects 2016 based on Java Data Mining

Relevance Feedback Algorithms Inspired By Quantum Detection

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Relevance Feedback Algorithms Inspired By Quantum Detection

Information Retrieval (IR) is concerned with indexing and retrieving documents including information relevant to a user’s information need. For improving Information Retrieval (IR) a class of algorithms is used called Relevance Feedback (RF) which consists of gathering and data representation of user’s information and automatically creating a new query.

To re-weight the query terms and to re-rank the document retrieved by an IR system, the proposed system provides a class of RF algorithms inspired by quantum detection. These algorithms project the query vector on a subspace spanned by the eigenvector which maximizes the distance between the distribution of quantum probability of relevance and the distribution of quantum probability of non-relevance.

The experiments showed that the RF algorithms inspired by quantum detection can outperform the state-of-the-art algorithms.Relevance Feedback Algorithms Inspired By Quantum Detection.

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