A Textual Filtering of HOG-Based Hierarchical Clustering of Lifelog Data

Abstract

In this paper we address the issue of life logging information retrieval and we introduce an approach that uses the output of a hierarchical clustering of data via assessing word similarities. Word similarity is computed using WordNet and Retina ontologies. We have tested our method during the 2017 ImageCLEF Lifelog challenge, the Summarization subtask. We discuss the performance, limitations and future improvements of our method.

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Cite this paper

@inproceedings{Dogariu2017ATF, title={A Textual Filtering of HOG-Based Hierarchical Clustering of Lifelog Data}, author={Mihai Dogariu and Bogdan Ionescu}, booktitle={CLEF}, year={2017} }