8 citations · 14 across the 5 of their papers we have counts for
7 papers
TREMOR: Template Matching for Large Seismic Data Collections
Manos Chatzakis, Rodrigo Flores-Allende, Mikael Freire +3
Seismic station networks continuously record the ground velocity at several locations on earth in the form of waveform data series, which seismologists analyze to detect various ki…
VADER: Filtered Vector Search with Declarative Recall
Manos Chatzakis, Duo Lu, Helena Caminal +7
Approximate filtered vector search (FVS), a core operation in many data management tasks that combine structured data with vector embeddings, exhibits increased complexity due to t…
An In-Depth Study of Filter-Agnostic Vector Search on a PostgreSQL Database System: [Experiments and Analysis]
Duo Lu, Helena Caminal, Manos Chatzakis +4
Filtered Vector Search (FVS) is critical for supporting semantic search and GenAI applications in modern database systems. However, existing research most often evaluates algorithm…
DaiSy: A Library for Scalable Data Series Similarity Search
Francesca Del Gaudio, Manos Chatzakis, Gayathiri Ravendirane +2
Exact similarity search over large collections of data series is a fundamental operation in modern applications, yet existing solutions are often fragmented, specialized, or tailor…
DARTH: Declarative Recall Through Early Termination for Approximate Nearest Neighbor Search
Manos Chatzakis, Yannis Papakonstantinou, Themis Palpanas
Approximate Nearest Neighbor Search (ANNS) presents an inherent tradeoff between performance and recall (i.e., result quality). Each ANNS algorithm provides its own algorithm-depen…
Optimizing Context-Enhanced Relational Joins
Viktor Sanca, Manos Chatzakis, Anastasia Ailamaki
Collecting data, extracting value, and combining insights from relational and context-rich multi-modal sources in data processing pipelines presents a challenge for traditional rel…
Odyssey: A Journey in the Land of Distributed Data Series Similarity Search
Manos Chatzakis, Panagiota Fatourou, Eleftherios Kosmas +2
This paper presents Odyssey, a novel distributed data-series processing framework that efficiently addresses the critical challenges of exhibiting good speedup and ensuring high sc…