This chapter highlights the benefits of semantics for analysis of the collaboration network in a bibliography dataset. The metadata of publications can be used for extracting keywords and terms, which can be the starting point towards building a taxonomy of topics. The aggregated effect of all publications of an author can determine his/her areas of expertise. We highlight the value of using a ...

Growing image collections have created a need for effective retrieval mechanisms. Although content-based image retrieval systems have made huge strides in the last decade, they often are not sufficient by themselves. Many databases, such as those at Flickr are augmented by keywords supplied by its users. A big stumbling block however lies in the fact that many keywords are actually similar or o...

Taxonomy construction is a resource-demanding, top down, and time consuming effort. It does not always cater for the prevailing context of the captured information. This paper proposes a novel approach to automatically convert tags into a hierarchical taxonomy. Folksonomy describes the process by which many users add metadata in the form of keywords or tags to shared content. Using folksonomy a...

A hierarchical framework is proposed to address the issues of modeling different type of words in keyword spotting (KWS). Keyword models are built at various levels according to the availability of training set resources for each individual word. The proposed approach improves the performance of KWS even when no training speech is available for the keywords. It also suggests an easier way to co...

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