35 citations · 89 across the 6 of their papers we have counts for
6 papers
Toward Efficient and Scalable Design of In-Memory Graph-Based Vector Search
Ilias Azizi, Karima Echihab, Themis Palpanas +1
Vector data is prevalent across business and scientific applications, and its popularity is growing with the proliferation of learned embeddings. Vector data collections often reac…
Graph-Based Vector Search: An Experimental Evaluation of the State-of-the-Art
Ilias Azizi, Karima Echihabi, Themis Palpanas
Vector data is prevalent across business and scientific applications, and its popularity is growing with the proliferation of learned embeddings. Vector data collections often reac…
ProS: Data Series Progressive k-NN Similarity Search and Classification with Probabilistic Quality Guarantees
Karima Echihabi, Theophanis Tsandilas, Anna Gogolou +2
Existing systems dealing with the increasing volume of data series cannot guarantee interactive response times, even for fundamental tasks such as similarity search. Therefore, it…
Hercules Against Data Series Similarity Search
Karima Echihabi, Panagiota Fatourou, Kostas Zoumpatianos +2
We propose Hercules, a parallel tree-based technique for exact similarity search on massive disk-based data series collections. We present novel index construction and query answer…
Return of the Lernaean Hydra: Experimental Evaluation of Data Series Approximate Similarity Search
Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas +1
Data series are a special type of multidimensional data present in numerous domains, where similarity search is a key operation that has been extensively studied in the data series…
The Lernaean Hydra of Data Series Similarity Search: An Experimental Evaluation of the State of the Art
Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas +1
Increasingly large data series collections are becoming commonplace across many different domains and applications. A key operation in the analysis of data series collections is si…