Browsing Data Science Institute by Title
Now showing items 356-375 of 544
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Random Indexing Explained with High Probability
(2015)Random indexing (RI) is an incremental method for constructing a vector space model (VSM) with a reduced dimensionality. Previously, the method has been justified using the mathematical framework of Kanerva's sparse ... -
Random indexing revisited
(Springer, 2015-05-17)Random indexing is a method for constructing vector spaces at a reduced dimensionality. Previously, the method has been proposed using Kanerva's sparse distributed memory model. Although intuitively plausible, this ... -
Random Manhattan Indexing
(2014)Vector space models (VSMs) are mathematically well-defined frameworks that have been widely used in text processing. In these models, high-dimensional, often sparse vectors represent text units. In an application, the ... -
Random Manhattan Integer Indexing: Incremental L1 Normed Vector Space Construction
(2014)Vector space models (VSMs) are mathematically well-defined frameworks that have been widely used in the distributional approaches to semantics. In VSMs, high-dimensional vectors represent linguistic entities. In an ... -
A random walk model for entity relatedness
(Springer Verlag, 2018-10-31)Semantic relatedness is a critical measure for a wide variety of applications nowadays. Numerous models, including path-based, have been proposed for this task with great success in many applications during the last few ... -
Rapid Competence Development in Serious Games Using Case-Based Reasoning and Threshold Concepts
(2010)A major challenge in todays fast pace world is the acquisition of competence in a timely and efficient manner, whilst keeping the individual highly motivated. This paper presents a novel based on the use of serious games ... -
RCE-NN: a five-stage pipeline to execute neural networks (CNNs) on resource-constrained IoT edge devices
(Association for Computing Machinery (ACM), 2020-10-06)Microcontroller Units (MCUs) in edge devices are resource constrained due to their limited memory footprint, fewer computation cores, and low clock speeds. These limitations constrain one from deploying and executing machine ... -
RDFS & OWL Reasoning for Linked Data
(na, 2013)Linked Data promises that a large portion of Web Data will be usable as one big interlinked RDF database against which structured queries can be answered. In this lecture we will show how reasoning - using RDF Schema (RDFS) ... -
Re-coding Black Mirror Chairs' Welcome & Organization
(ACM, 2018-04-23)This volume of proceedings presents the papers from the 2nd edition of the interdisciplinary workshop Re-coding Black Mirror, held on April 24, 2018 in Lyon, France and co-located with The WEB Conference (WWW2018). ... -
ReConRank: A Scalable Ranking Method for Semantic Web Data with Context
(2006)We present an approach that adapts the well-known PageRank/HITS algorithms to Semantic Web data. Our method combines ranks from the RDF graph with ranks from the context graph, i.e. data sources and their linkage. We present ... -
Reconstruction of Threaded Conversations in Online Discussion Forums
(Fifth International AAAI Conference on Weblogs and Social Media, 2011-07-18)[no abstract available] -
Regularizing knowledge graph embeddings via equivalence and inversion axioms
(Springer Verlag, 2017-12-30)Learning embeddings of entities and relations using neural architectures is an effective method of performing statistical learning on large-scale relational data, such as knowledge graphs. In this paper, we consider the ... -
Relaxing the Basic KR&R Principles to Meet the Emergent Semantic Web
(CEUR-WS, 2008)The paper argues for an alternative, empirical (instead of analytical) approach to a Semantic Web-ready KR&R, motivated by the so far largely untackled need for a feasible emergent content processing. -
Renewable energy integration through coalition formation for P2P energy trading
(National University of Ireland Galway, 2020-10-09)Renewable energy sources are highly unreliable; hence prosumers connected to renewable energy sources find unreliable energy surplus and demands which should be managed frequently within neighbourhoods. Peer-to-peer(P2P) ... -
Rewriting simplified text into a controlled natural language
(IOS Press, 2018-08-27)While machine processable Controlled Natural Languages (CNLs) as a natural language interface have proven a popular, unambiguous and user friendly method for non experts to engineer formal knowledge-bases, human-oriented ... -
A Roadmap for navigating the Life Sciences Linked Open Data Cloud
(2014)Multiple datasets that add high value to biomedical research have been exposed on the web as a part of the Life Sciences Linked Open Data (LSLOD) Cloud. The ability to easily navigate through these datasets is crucial for ... -
The Role of Community-Driven Data Curation for Enterprises
(Springer US, 2010)With increased utilization of data within their operational and strategic processes, enterprises need to ensure data quality and accuracy. Data curation is a process that can ensure the quality of data and its fitness ...