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The World Wide Web has become a huge repository of data of interest for a variety of application domains. However, the same features that have made the Web so useful and popular also impose important restrictions on the way the data it contains can be manipulated. Particularly, in the traditional Web scenario, there is an inherent difficulty in gaining access to data that is implicitly present in...
Large unstructured photo collections from Internet usually have distinguishable keyword tagging associated with the images. Photos from tourist and heritage sites can be described with detailed and part-wise annotations resulting in an improved automatic search and enhanced photo browsing experience. Manually
This paper proposes a symbol feature-based hidden Markov model (HMM). Each state in the model is expressed by some symbol features, and is described by feature lists that draw from regular expressions and text inference; based on which, we use Viterbi Algorithm to extract the information from scientific researcherspsila homepages. It works well although there is great information redundancy.
in front of him/her by the shutter clicks. One of the great advantages of our approach is to use open image database such as Flickr, Picasa, or so on, to identify a landmark. Images on such open databases are automatically updated and some proper keywords are given by photographers in the world. Therefore, we need not
similar product images on shopping websites, ranking product tags by text aggregation, and re-search textual items consisting of semantic meaningful tags to make a recommendation. In addition, users can choose automatically suggested keywords to reflect their intentions. Subjective evaluation has demonstrated the
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