We propose a novel attention network for document annotation with user-generated tags. The network is designed according to the human reading and annotation behaviour. Usually, users try to digest the title and obtain a rough idea about the topic first, and then read the content of the document. Present research shows that the title metadata could largely affect the social annotation. To better utilise this information, we design a framework that separates the title from the content of a document and apply a title-guided attention mechanism over each sentence in the content. We also propose two semanticbased loss regularisers that enforce the output of the network to conform to label semantics, i.e. similarity and subsumption. We analyse each part of the proposed system with two real-world open datasets on publication and question annotation. The integrated approach, Joint Multi-label Attention Network (JMAN), significantly outperformed the Bidirectional Gated Recurrent Unit (Bi-GRU) by around 13%-26% and the Hierarchical Attention Network (HAN) by around 4%-12% on both datasets, with around 10%-30% reduction of training time.
T. Tietz, J. Waitelonis, K. Zhou, P. Felgentreff, N. Meyer, A. Weber, and H. Sack. Proceedings of the Posters and Demo Track of the 15th International Conference on Semantic Systems co-located with 15th International Conference on Semantic Systems (SEMANTiCS 2019), Karlsruhe, Germany, September 9th - to - 12th, 2019, volume 2451 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)
G. Gesese, M. Alam, and H. Sack. Proceedings of the Workshop on Deep Learning for Knowledge Graphs (DL4KG2020) co-located with the 17th Extended Semantic Web Conference 2020 (ESWC 2020), Heraklion, Greece, June 02, 2020 - moved online, volume 2635 of CEUR Workshop Proceedings, CEUR-WS.org, (2020)
M. Alam, H. Birkholz, D. Dess\`ı, C. Eberl, H. Fliegl, P. Gumbsch, P. von Hartrott, L. Mädler, M. Niebel, H. Sack and 1 other author(s). Joint Proceedings of the Semantics co-located events: Poster&Demo track and Workshop on Ontology-Driven Conceptual Modelling of Digital Twins co-located with Semantics 2021, Amsterdam and Online, September 6-9, 2021, volume 2941 of CEUR Workshop Proceedings, CEUR-WS.org, (2021)
T. Dong, and M. Khosla. 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), page 1835-1842. Los Alamitos, CA, USA, IEEE Computer Society, (December 2020)