Browsing Data Science Institute by Title
Now showing items 308-327 of 466
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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 ... -
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. -
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 ... -
The role of negative results for choosing an evaluation approach - a recommender systems case study
(CEUR Workshop Proceedings, 2015-06-01)We describe a case study, which shows how important negative results are in uncovering biased evaluation methodologies. Our re- search question is how to compare a recommender algorithm that uses an RDF graph to a ... -
The role of open data in driving sustainable mobility in nine smart cities
(Association for Information Systems, 2017-06-05)In today’s era of globalization, sustainable mobility is considered as a key factor in the economic growth of any country. With the emergence of open data initiatives, there is tremendous potential to improve mobility. ...