Textual queries are largely employed in information retrieval to let users specify search goals in a natural way. However, di erences in user and system terminologies can challenge the identi cation of the user's information needs, and thus the generation of relevant results. We argue that the explicit management of ontological knowledge, and of the meaning of concepts (by integrating linguistic and encyclopaedic knowledge in the system ontology), can improve the analysis of search queries, because it enables a exible identi cation of the topics the user is searching for, regardless of the adopted vocabulary. is paper proposes an information retrieval support model based on semantic concept identi cation. Starting from the recognition of the ontology concepts that the search query refers to, this model exploits the quali ers speci ed in the query to select information items on the basis of possibly ne-grained features. Moreover, it supports query expansion and reformulation by suggesting the exploration of semantically similar concepts, as well as of concepts related to those referred in the query through thematic relations. A test on a data-set collected using the OnToMap Participatory GIS has shown that this approach provides accurate results.
Authors in REF contended that general and similar concepts related to the original query can be identified using thematic relations of ontology.
Concept-aware Geographic Information Retrieval
Proceedings of the International Conference on Web Intelligence (WI 2017)
Computer Science