our findings in terms of the performance of various query processing tasks such as Boolean and ranked intersection for the different indices and discuss which index type would be appropriate under different conditions for semantic search....

This paper addresses the task of document retrieval based on the degree of document relatedness to the meanings of a query by presenting a semantic-enabled language model. Our model relies on the use of semantic linking ...

Neural embeddings have been effectively integrated into information retrieval tasks including ad hoc retrieval. One of the benefits of neural embeddings is they allow for the calculation of the similarity between queries ...

Semantic search has emerged as a possible way for addressing the challenges of traditional keyword-based retrieval systems such as the vocabulary gap between the query and document spaces. In this paper, we propose a novel semantic retrieval...

Recent developments have shown that entity-based models that rely on information from the

knowledge graph can improve document retrieval performance. However, given the non-transitive

nature of relatedness ...