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Content based video retrieval via spatial-temporal information discovery. (2013)
Thesis
WANG, L. 2013. Content based video retrieval via spatial-temporal information discovery. Robert Gordon University, PhD thesis.

Content based video retrieval (CBVR) has been strongly motivated by a variety of realworld applications. Most state-of-the-art CBVR systems are built based on Bag-of-visual- Words (BovW) framework for visual resources representation and access. The f... Read More about Content based video retrieval via spatial-temporal information discovery..

You have e-mail, what happens next? Tracking the eyes for genre. (2013)
Journal Article
CLARK, M., RUTHVEN, I., HOLT, P.O'B., SONG, D. and WATT, S. 2014. You have e-mail, what happens next? Tracking the eyes for genre. Information processing and management [online], 50(1), pages 175-198. Available: https://doi.org/10.1016/j.ipm.2013.08.005

This paper reports on an approach to the analysis of form (layout and formatting) during genre recognition recorded using eye tracking. The researchers focused on eight di erent types of e-mail, such as calls for papers, newsletters and spam, which w... Read More about You have e-mail, what happens next? Tracking the eyes for genre..

Hybrid models for combination of visual and textual features in context-based image retrieval. (2013)
Thesis
KALICIAK, L. 2013. Hybrid models for combination of visual and textual features in context-based image retrieval. Robert Gordon University, PhD thesis.

Visual Information Retrieval poses a challenge to intelligent information search systems. This is due to the semantic gap, the difference between human perception (information needs) and the machine representation of multimedia objects. Most existing... Read More about Hybrid models for combination of visual and textual features in context-based image retrieval..

Approximating true relevance model in relevance feedback. (2013)
Thesis
ZHANG, P. 2013. Approximating true relevance model in relevance feedback. Robert Gordon University, PhD thesis.

Relevance is an essential concept in information retrieval (IR) and relevance estimation is a fundamental IR task. It involves not only document relevance estimation, but also estimation of user's information need. Relevance-based language model aims... Read More about Approximating true relevance model in relevance feedback..