This research focusing on using semantic embedding to improve the performance of Information Retrieval (IR) about the Covid-19 related data. According to previous researches, the technology of word embedding can significantly improve the performance of IR. There are many types of semantic embedding models at present. The purpose of this research is not to develop a new one, but to combine multiple popular semantic embedding models and find a more effective ranking for retrieving a better IR result by a comparative analysis of these semantic embedding technologies. Besides, the current embeddings are mostly based on words, phrases, or documents, not on entities. So, providing the entity-based IR function, which is missing in PubMed or other search engines like Google, is another goal of this research. The expected outcome of this research is an entity-based working prototype focusing on the Covid-19 data, which can visually mark the differences between the search results of different semantic embedding models.
The Research Project is a research project that serves as an exercise for the master’s thesis. As such it serves to give master students who did their bachelor study elsewhere the experience that bachelor students from the UT obtained during their bachelor project.
View the full research paper for this project.
This research focusing on using semantic embedding to improve the performance of Information Retrieval (IR) about the Covid-19 related data. According to previous researches, the technology of word embedding can significantly improve the performance of IR. There are many types of semantic embedding models at present. The purpose of this research is not to develop a new one, but to combine multiple popular semantic embedding models and find a more effective ranking for retrieving a better IR result by a comparative analysis of these semantic embedding technologies. Besides, the current embeddings are mostly based on words, phrases, or documents, not on entities. So, providing the entity-based IR function, which is missing in PubMed or other search engines like Google, is another goal of this research. The expected outcome of this research is an entity-based working prototype focusing on the Covid-19 data, which can visually mark the differences between the search results of different semantic embedding models.
The Research Project is a research project that serves as an exercise for the master’s thesis. As such it serves to give master students who did their bachelor study elsewhere the experience that bachelor students from the UT obtained during their bachelor project.
View the full research paper for this project.