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Explore FREDDY: Fast Word Embeddings in Database Systems 

BTW 2019 Günther, Michael; Thiele, Maik; Lehner, Wolfgang; Yanakiev, Zdravko
Word embeddings encode a lot of semantic as well as syntactic features and therefore are useful in many tasks especially in Natural Language Processing and Information Retrieval. FREDDY (Fast woRd EmbedDings Database sYstems), an extended PostgreSQL database system, allowing the user to analyze structured knowledge in ...

BTW2019 - Datenbanksysteme für Business, Technologie und WebBTW2019 - Datenbanksysteme für Business, Technologie und Web 

BTW 2019 Grust, Torsten; Naumann, Felix; Böhm, Alexander; Lehner, Wolfgang; Härder, Theo; Rahm, Erhard; Heuer, Andreas; Klettke, Meike; Meyer, Holger

Understanding Trolls with Efficient Analytics of Large Graphs in Neo4j 

BTW 2019 Allen, David; Hodler, Amy; Hunger, Michael; Knobloch, Martin; Lyon, William; Needham, Mark; Voigt, Hannes
Analytics of large graph data set has become an important means of understanding and influencing the world. The use of graph database technology in the International Consortium of Investigative Journalists’ (ICIJ) investigation of the Panama Papers and Paradise Papers or in cancer research illustrates how analysing ...

Ganzheitliches Metadatenmanagement im Data Lake: Anforderungen, IT-Werkzeuge und Herausforderungen in der Praxis 

BTW 2019 Gröger, Christoph; Hoos, Eva
Data Lakes haben sich in der industriellen Praxis als Plattformen für die Speicherung und Analyse aller Arten von (Roh-)daten etabliert. Erweiterte Anforderungen hinsichtlich Governance und Self-Service machen das Metadatenmanagement im Data Lake zum kritischen Erfolgsfaktor. Bisher gibt es dazu jedoch nur wenige ...

Perceptual Relational Attributes: Navigating and Discovering Shared Perspectives from User-Generated Reviews 

BTW 2019 Lofi, Christoph; Valle Torre, Manuel; Ye, Mengmeng
Effectively modelling and querying experience items like movies, books, or games in databases is challenging because these items are better described by their resulting user experience or perceived properties than by factual attributes. However, such information is often subjective, disputed, or unclear. Thus, social ...

In-Database Machine Learning: Gradient Descent and Tensor Algebra for Main Memory Database Systems 

BTW 2019 Schüle, Maximilian; Simonis, Frédéric; Heyenbrock, Thomas; Kemper, Alfons; Günnemann, Stephan; Neumann, Thomas
Machine learning tasks such as regression, clustering, and classification are typically performed outside of database systems using dedicated tools, necessitating the extraction, transfor-mation, and loading of data. We argue that database systems when extended to enable automatic differentiation, gradient descent, and ...

IBM Cloud Databases: Turning Open Source Databases Into Cloud Services 

BTW 2019 Waizenegger, Tim; Lumpp, Thomas
Databases in all their forms are the backbone of most applications, running in the Cloud or on-premise. This creates a large demand for hosted, as-a-service database systems that are used either by Cloud applications, or even by on-premise applications. Through this demand, two types of offerings were created: new ...

Eliminating the Bandwidth Bottleneck of Central Query Dispatching Through TCP Connection Hand-Over 

BTW 2019 Klauck, Stefan; Plauth, Max; Knebel, Sven; Strobl, Marius; Santry, Douglas; Eggert, Lars
In scale-out database architectures, client queries must be routed to individual backend database servers for processing. In dynamic database systems, where backend servers join and leave a cluster or data partitions move between servers, clients do not know which server to send queries to. Using a central dispatcher, ...

The Best of Both Worlds: Combining Hand-Tuned and Word-Embedding-Based Similarity Measures for Entity Resolution 

BTW 2019 Chen, Xiao; Campero Durand, Gabriel; Zoun, Roman; Broneske, David; Li, Yang; Saake, Gunter
Recently word embedding has become a beneficial technique for diverse natural language processing tasks, especially after the successful introduction of several popular neural word embedding models, such as word2vec, GloVe, and FastText. Also entity resolution, i.e., the task of identifying digital records that refer to ...

Graph Data Transformations in Gradoop 

BTW 2019 Kricke, Matthias; Peukert, Eric; Rahm, Erhard
The analysis of graph data using graph database and distributed graph processing systems has gained significant interest. However, relatively little effort has been devoted to preparing the graph data for analysis, in particular to transform and integrate data from different sources. To support such ETL processes for ...
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Gesellschaft für Informatik e.V. (GI), Kontakt: Geschäftsstelle der GI
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Author

Lehner, Wolfgang (5)Neumann, Thomas (4)Broneske, David (3)Kemper, Alfons (3)Rahm, Erhard (3)Saake, Gunter (3)Sattler, Kai-Uwe (3)Zoun, Roman (3)Arning, Ann-Katrin (2)Günther, Michael (2)... View More

Subject

Indexing (2)NoSQL (2)word embeddings (2)accelerator (1)Adaptivity (1)Analytics (1)Apache SystemML (1)approximated nearest neighbor search (1)B-tree (1)Backend/Database Co-Design (1)... View More

Date Issued

2019 (47)

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Yes (47)

About uns | FAQ | Help | Imprint | Datenschutz

Gesellschaft für Informatik e.V. (GI), Kontakt: Geschäftsstelle der GI
Diese Digital Library basiert auf DSpace.