Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Perez, Arnau"'
Autor:
Perez, Arnau, Vizcaino, Xavier
Retrieval Augmented Generation (RAG) systems struggle with processing multimodal documents of varying structural complexity. This paper introduces a novel multi-strategy parsing approach using LLM-powered OCR to extract content from diverse document
Externí odkaz:
http://arxiv.org/abs/2412.15262
Autor:
Szárnyas, Gábor, Bebee, Brad, Birler, Altan, Deutsch, Alin, Fletcher, George, Gabb, Henry A., Gosnell, Denise, Green, Alastair, Guo, Zhihui, Hare, Keith W., Hidders, Jan, Iosup, Alexandru, Kiryakov, Atanas, Kovatchev, Tomas, Li, Xinsheng, Libkin, Leonid, Lin, Heng, Luo, Xiaojian, Prat-Pérez, Arnau, Püroja, David, Qi, Shipeng, van Rest, Oskar, Steer, Benjamin A., Szakállas, Dávid, Tong, Bing, Waudby, Jack, Wu, Mingxi, Yang, Bin, Yu, Wenyuan, Zhang, Chen, Zhang, Jason, Zhou, Yan, Boncz, Peter
Graph data management is instrumental for several use cases such as recommendation, root cause analysis, financial fraud detection, and enterprise knowledge representation. Efficiently supporting these use cases yields a number of unique requirements
Externí odkaz:
http://arxiv.org/abs/2307.04350
Autor:
Iosup, Alexandru, Musaafir, Ahmed, Uta, Alexandru, Pérez, Arnau Prat, Szárnyas, Gábor, Chafi, Hassan, Tănase, Ilie Gabriel, Nai, Lifeng, Anderson, Michael, Capotă, Mihai, Sundaram, Narayanan, Boncz, Peter, Depner, Siegfried, Heldens, Stijn, Manhardt, Thomas, Hegeman, Tim, Ngai, Wing Lung, Xia, Yinglong
In this document, we describe LDBC Graphalytics, an industrial-grade benchmark for graph analysis platforms. The main goal of Graphalytics is to enable the fair and objective comparison of graph analysis platforms. Due to the diversity of bottlenecks
Externí odkaz:
http://arxiv.org/abs/2011.15028
The abundance of interconnected data has fueled the design and implementation of graph generators reproducing real-world linking properties, or gauging the effectiveness of graph algorithms, techniques and applications manipulating these data. We con
Externí odkaz:
http://arxiv.org/abs/2001.07906
Autor:
Angles, Renzo, Antal, János Benjamin, Averbuch, Alex, Birler, Altan, Boncz, Peter, Búr, Márton, Erling, Orri, Gubichev, Andrey, Haprian, Vlad, Kaufmann, Moritz, Pey, Josep Lluís Larriba, Martínez, Norbert, Marton, József, Paradies, Marcus, Pham, Minh-Duc, Prat-Pérez, Arnau, Püroja, David, Spasić, Mirko, Steer, Benjamin A., Szakállas, Dávid, Szárnyas, Gábor, Waudby, Jack, Wu, Mingxi, Zhang, Yuchen
The Linked Data Benchmark Council's Social Network Benchmark (LDBC SNB) is an effort intended to test various functionalities of systems used for graph-like data management. For this, LDBC SNB uses the recognizable scenario of operating a social netw
Externí odkaz:
http://arxiv.org/abs/2001.02299
Autor:
Prat-Pérez, Arnau, Guisado-Gámez, Joan, Salas, Xavier Fernández, Koupy, Petr, Depner, Siegfried, Bartolini, Davide Basilio
The use of synthetic graph generators is a common practice among graph-oriented benchmark designers, as it allows obtaining graphs with the required scale and characteristics. However, finding a graph generator that accurately fits the needs of a giv
Externí odkaz:
http://arxiv.org/abs/1704.00630
The search for relevant information can be very frustrating for users who, unintentionally, use too general or inappropriate keywords to express their requests. To overcome this situation, query expansion techniques aim at transforming the user reque
Externí odkaz:
http://arxiv.org/abs/1602.07217
Autor:
Guisado-Gámez, Joan, Prat-Pérez, Arnau
Knowledge bases are very good sources for knowledge extraction, the ability to create knowledge from structured and unstructured sources and use it to improve automatic processes as query expansion. However, extracting knowledge from unstructured sou
Externí odkaz:
http://arxiv.org/abs/1505.01306
Community detection has become an extremely active area of research in recent years, with researchers proposing various new metrics and algorithms to address the problem. Recently, the Weighted Community Clustering (WCC) metric was proposed as a nove
Externí odkaz:
http://arxiv.org/abs/1411.0557
Community detection has arisen as one of the most relevant topics in the field of graph data mining due to its importance in many fields such as biology, social networks or network traffic analysis. The metrics proposed to shape communities are gener
Externí odkaz:
http://arxiv.org/abs/1207.6269