Semantic Spatio-Textual Similarity Search (SSTSS)
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Keywords
Ευρετηρίαση ; Χωρο-κειμενικά δεδομένα ; Πολυδιάστατες αναπαραστάσεις ; Κ-Μέσοι ; Προσεγγιστική ευρετηρίασηAbstract
In this thesis, we address the problem of semantic similarity search over spatio-textual data. In contrast with most existing works on spatial-keyword search that rely on exact matching of query key-words to textual descriptions, we focus on semantic textual similarity using word embeddings, which have been shown to capture semantic similarity exceptionally well in practice. To support efficient search, we propose a novel indexing approach (called CSSI) that ensures correctness of results, alongside its approximate variant (called CSSIA) that introduces a small amount of error in exchange for improved performance. Both variants are based on a hybrid scheme that indexes both spatial and textual/semantic information at the same time, achieving high pruning percentages and improved performance and scalability.