Uyo, Nigeria, November 18-19, 2021
Speech and language therapies are often provided through direct interaction between patient and therapist trough a set of activities developed by the therapist for the diagnosis and treatment of patients’ disorders in various parts of the world. The direct interaction gives personal feedback to every patient. Speech therapy generally involves extended interaction, but there are insufficient resources to provide these services for a growing population of disabled patients. Providing this therapy for all impaired patients is impracticable. The advent of semantic web provides a window to make this therapeutic tool available for patients and skilled therapists. Researches around the semantic web welcomes applications on several domains including speech and language therapies across under-resourced languages.
The use of Natural Language Processing (NLP) approaches in solving human language is often deployed where there is need for domain information extraction, machine translation, search and summarization. Successes have been reported on the impact of domain knowledge on data analysis and vice versa. These successes include those on pre-processing data, searching data, redundancy and inconsistency data, knowledge engineering, domain concepts and relationships extraction, etc. The domain knowledge requires structured representation to facilitate data sharing and reuse (access). This is provided through the use of ontologies and knowledge graphs. Modeling data representations with many layers of non-linear transformations requires the use of deep learning (DL). Hence, we see the link and combination of NLP, Ontologies, Knowledge graphs and DL as adequate tools to providing therapeutic multilingual solutions on the semantic web. This will help in data analysis, knowledge representation interpretation and possible decision generation as therapy.
The underlying tasks are grouped as follows:
- Group 1: ontology population, ontology extension, ontology learning, ontology alignment and integration, fuzzy-ontology modeling
- Group 2: semantic graph embedding, latent semantic representation, knowledge graphs, hybrid embedding (symbolic and semantic representations)
- Group 3: summarization, translation, named entity recognition, question answering, document classification, etc.
- Group 4: parsing (part-of-speech tagging), tokenization, sentence detection, dependency parsing, semantic role labeling, semantic dependency parsing, etc.
This workshop aims at demonstrating recent and future advances in deep learning by using Semantic Web and its underlying technology and NLP techniques which can provide therapeutic solutions multilingual problems particularly among under-resourced languages. Also, results of on-going research in natural language processing, structured knowledge representations (featuring ontologies and knowledge graphs) and deep learning approaches as they are used by experts from industry, science and academia are encouraged for discussions.
We invite submission of original related researches, but are not limited to the topics below.8
Topics of interests:
- Construction ontology embeddings
- Ontology-based text classification
- Learning ontology embeddings
- Semantic role labelling
- Ontology reasoning with Deep Neural Networks
- Deep learning for ontological semantic annotations
- Spatial and temporal ontology embeddings
- Integrating Fuzzy Logic with Ontology
- Ontology alignment and matching based on deep learning models
- Ontology learning from text using deep learning models
- Knowledge Graphs
- Unsupervised Learning
- Text classification using deep models
- Neural machine translation
- Deep question answering
- Deep text summarization
- Deep speech recognition
The workshop is open to submit unpublished work resulting from researches that present original scientific results, methodological aspects, concepts and approaches. All submissions must be PDF documents written in English and formatted according to LNCS instructions for authors. Papers are to be submitted through the workshop’s EasyChair submission page.
We welcome the following types of contributions:
- Full research papers (8-10 pages): Finished or consolidated R&D works, to be included in one of the Workshop topics
- Short papers (4-6 pages): Ongoing works with relevant preliminary results, opened to discussion.
At least one author of each accepted paper must register for the workshop, in order to present the paper, there, and to the conference. For further instructions please refer to the KGSWC 2021 page.
- Workshop paper submission due: July 30, 2021
- Workshop paper notifications: September 15, 2021
- Workshop paper camera-ready versions due: October 15, 2021
- Workshop: November 18-19, 2021
All deadlines are 23:59 anywhere on earth (WAT -12).
All accepted workshop papers will be published in a book. The best papers from this workshop may be included in the supplementary proceedings of KGSWC 2021.
Patience Usoro Usip <firstname.lastname@example.org>