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Selection and aggregation of ranking criteria became an important topic in information retrieval as search is getting more specialized and as volume of electronically available information grows. In this context, document ranking has undergone a shift from ...
One of the key challenges to realize automated processing of the information on the Web, which is the central goal of the Semantic Web, is related to the entity matching problem. There are a number of tools that reliably recognize named entities, such as p ...
HMM state mapping with the Kullback-Leibler divergence as a distribution similarity measure is a simple and effective technique that enables cross-lingual speaker adaptation for speech synthesis. However, since this technique does not take any other potent ...
The Probabilistic Latent Semantic indexing model, introduced by T. Hofmann (1999), has engendered applications ill numerous fields, notably document classification and information retrieval. In this context, the Fisher kernel was found to be an appropriate ...
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In conventional vector space model for information retrieval, query vector generation is imperfect for retrieval of precise documents which are de-sired by user. In this paper, we present a stochastic based approach for optimiz-ing query vector without use ...
ABSTRACT. An information-geometric approach for document similarities in the framework of “Probabilistic Latent Semantic Indexing” was first proposed by T. Hofmann (2000) and later extended (“revisited”) by Nyffenegger et al. (2006). This paper presents an ...
In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. This identific ...
In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. Thisidentifica ...
In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. This identific ...
The Probalistic Latent Semantic Indexing model, introduced by T. Hofmann (1999), has engendered applications in numerous fields, notably document classification and information retrieval. In this context, the Fisher kernel was found to be an appropriate do ...