Natural Language Understanding
It is a subtopic of Natural Language Processing that deals with machine reading comprehension, extracting meaning from natural language text.
Hakimov, S. (2019). Learning Multilingual Semantic Parsers for Question Answering over Linked Data. A comparison of neural and probabilistic graphical model architectures. Bielefeld University, Germany (Doctoral Dissertation) PDF
Hakimov, S. , Jebbara, S., Cimiano, P. (2019). Evaluating Architectural Choices for Deep Learning Approaches for Question Answering over Knowledge Bases. In Proceedings of the 13th International Semantic Computing Conference (ICSC) PDF
Ell B, Hakimov, S. , Braukmann, P., Cazzoli, L., Kaupmann, F., Mancino, A., Altaf Memon, J., Rother, K., Saini, A., Cimiano, P. (2017). Towards a Large Corpus of Richly Annotated Web Tables for Knowledge Base Population. In Proceedings of 5th International Workshop on Linked Data for Information Extraction, co-located with the 16th International Semantic Web Conference (ISWC) PDF
Hakimov, S., Jebbara, S., Cimiano, P. (2017). AMUSE: Multilingual Semantic Parsing for Question Answering over Linked Data. In Proceedings of the 16th International Semantic Web Conference (ISWC) PDF
Ell, B., Hakimov, S., Cimiano, P. (2016). Statistical Induction of Coupled Domain/Range Restrictions from RDF Knowledge Bases. In Proceedings of 4th NLP and DBpedia Workshop, co-located with the 15th International Semantic Web Conference (ISWC) PDF
Hakimov, S., ter Horst, H., Jebbara, S., Hartung, M., Cimiano, P. (2016). Combining textual and graph-based features for named entity disambiguation using undirected probabilistic graphical models. In Proceedings of 20th International Knowledge Engineering and Knowledge Management Conference (EKAW) PDF
Hakimov, S., Unger, C., Walter, S., Cimiano, P. (2015) Applying semantic parsing to question answering over linked data: Addressing the lexical gap. In Proceedings of International Conference on Applications of Natural Language to Information Systems (NLDB) PDF
Dogdu, E., Hakimov, S., Yumusak, S. (2014). A data-model driven web application development framework. In Proceedings of the 2014 ACM Southeast Regional Conference PDF
Hakimov, S. (2013). Named Entity Disambiguation using Linked Open Data. TOBB University, Ankara, Turkey (Master's Thesis) PDF
Hakimov, S., Tunc, H., Akimaliev, M., Dogdu, E. (2013) Semantic question answering system over linked data using relational patterns. In Proceedings of the Joint EDBT/ICDT 2013 Workshops PDF
Hakimov, S., Oto, S. A., Dogdu, E. (2012). Named entity recognition and disambiguation using linked data and graph-based centrality scoring. In Proceedings of the 4th international workshop on semantic web information management PDF
It deals with providing a summary for lengthy videos by taking into account the audio, text and visual frames to create concise, informative summaries. The research mainly deals with educational videos where the aim is to provide short summaries that cover most of the information presented in a video to boost easier and quick way for skimming seminar, research talks.
Ghauri, J.A., Hakimov, S. and Ewerth, R., (2021). Supervised Video Summarization via Multiple Feature Sets with Parallel Attention. In the Proceedings of IEEE International Conference on Multimedia and Expo (ICME) PDF Git repo
It is a field of study to detect documents that include falsified information in the form of text, images, videos, etc. The research explores the ideas to detect misinformed facts from social media posts, news articles, videos and related multimedia data.
Müller-Budack, E., Theiner, J., Diering, S., Idahl, M., Hakimov, S. and Ewerth, R., (2021). Multimodal news analytics using measures of cross-modal entity and context consistency. *International Journal of Multimedia Information Retrieval*, pp.1-15. PDF Git repo
Cheema, G.S., Hakimov, S., Müller-Budack, E. and Ewerth, R., (2021). On the Role of Images for Analyzing Claims in Social Media. In the Proceedings of the CLEOPATRA workshop co-located with The Web Conference (WWW) PDF Git repo
Cheema, G.S., Hakimov, S. and Ewerth, R., (2020). Check_square at CheckThat! 2020: Claim Detection in Social Media via Fusion of Transformer and Syntactic Features. In Proceedings of the Eleventh International Conference of the CLEF Association PDF Git repo
The goal is to analyse vast amounts of event-centric textual and visual information in multiple languages.
Müller-Budack, E., Springstein, M., Hakimov, S., Mrutzek, K. and Ewerth, R., (2021). Ontology-driven Event Type Classification in Images. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision PDF Git repo
Check out the CLEOPATRA Workshop