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Jaroslav Pokorny

Researcher at First Faculty of Medicine, Charles University in Prague

Publications -  52
Citations -  1138

Jaroslav Pokorny is an academic researcher from First Faculty of Medicine, Charles University in Prague. The author has contributed to research in topics: XML validation & Efficient XML Interchange. The author has an hindex of 13, co-authored 52 publications receiving 1084 citations. Previous affiliations of Jaroslav Pokorny include Charles University in Prague.

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Physiologic and Morphologic Characteristics of Granule Cell Circuitry in Human Epileptic Hippocampus

TL;DR: The data suggest that granule cell bursting activity is at least in part a function of compromised synaptic inhibition, since levels of γ‐aminobutyric acid (GABA) blockade that are generally subthreshold for burst induction were epileptogenic in some tissue samples from human epileptic hippocampus.
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NoSQL databases: a step to database scalability in web environment

TL;DR: The paper shows vary different data models and query possibilities in a common terminology enabling comparison and categorization of NoSQL databases, particularly their horizontal scalability and concurrency model.
Proceedings ArticleDOI

NoSQL databases: a step to database scalability in web environment

TL;DR: In context of cloud computing, architectures and basic features of these databases are studied, particularly their horizontal scalability and concurrency model, that is mostly weaker than ACID transactions in relational SQL-like database systems.
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A clustering-based prefetching scheme on a Web cache environment

TL;DR: This paper presents a clustering-based prefetching scheme where a graph-based clustering algorithm identifies clusters of ''correlated'' Web pages based on the users' access patterns that can be integrated easily into a Web proxy server, improving its performance.
Proceedings ArticleDOI

WordNet Ontology Based Model for Web Retrieval

TL;DR: This paper presents a basic method of mapping LSI concepts on given ontology (Word-Net), used both for retrieval recall improvement and dimension reduction.