Xiaozhao Zhao

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The classical bag-of-word models for information retrieval (IR) fail to capture contextual associations between words. In this article, we propose to investigate <i>pure high-order dependence</i> among a number of words forming an unseparable semantic entity, that is, the high-order dependence that cannot be reduced to the random coincidence of lower-order(More)
Quantum theory (QT) has recently been employed to advance the theory of information retrieval (IR). A typical method, namely the Quantum Probability Ranking Principle (QPRP), was proposed to re-rank top retrieved documents by considering the inter-dependencies between documents through the " quantum interference ". In this paper, we attempt to explore(More)
Copyright and Moral Rights for the articles on this site are retained by the individual authors and/or other copyright owners. For more information on Open Research Online's data policy on reuse of materials please consult the policies page. Abstract. The classical bag-of-word models fail to capture contextual associations between words. We propose to(More)
Estimating the probability of relevance for a document is fundamental in information retrieval. From a theoretical point of view, risk exists in the estimation process, in the sense that the estimated probabilities may not be the actual ones precisely. The estimation risk is often considered to be dependent on the rank. For example, the probability ranking(More)
Copyright and Moral Rights for the articles on this site are retained by the individual authors and/or other copyright owners. For more information on Open Research Online's data policy on reuse of materials please consult the policies page. Abstract. Query expansion, while generally effective in improving retrieval performance, may lead to the query-drift(More)
Recently, Quantum Theory (QT) has been employed to advance the theory of Information Retrieval (IR). Various analogies between QT and IR have been established. Among them, a typical one is applying the idea of photon polarization in IR tasks, e.g., for document ranking and query expansion. In this paper, we aim to further extend this work by constructing a(More)