Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Klara A. Weiand

dblp:59/6484 · DBLP profile ↗
← Back
6ranked-venue papers
1as first author
0since 2021 · last 2012
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 4 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 3Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
2 papers
Information retrieval · 61% Query processing and optimization · 30% Data models and query languages · 9%
Artificial intelligence
1 paper
Knowledge representation and reasoning · 100%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Knowledge representation and reasoning
knowledge management
0.112010
visKQWL, a visual renderer for a semantic web query language · WWW 2010
Knowledge, reasoning and agents › Knowledge representation and reasoning › ontology › semantic web
semantic wiki
0.112010
visKQWL, a visual renderer for a semantic web query language · WWW 2010
Information retrieval › search engines › web crawling
focused crawling
0.112010
Not so creepy crawler: easy crawler generation with standard xml queries · WWW 2010
Information retrieval › search engines
web crawling
0.112010
Not so creepy crawler: easy crawler generation with standard xml queries · WWW 2010
Query processing and optimization
XML query processing
0.112010
Not so creepy crawler: easy crawler generation with standard xml queries · WWW 2010

Methods — techniques the papers use, named apart from their topics

visual rendering · 0.2XML queries · 0.1
YearPublicationVenuePosition
2012 pest: Fast approximate keyword search in semantic data using eigenvector-based term propagation
Klara A. Weiand, Fabian Kneißl, Wojciech lobacz, Tim Furche, François Bry
Inf. Syst.1
2010 Flavors of KWQL, a Keyword Query Language for a Semantic Wiki
François Bry, Klara A. Weiand
SOFSEM2
2010 Not so creepy crawler: easy crawler generation with standard xml queries
abstract
Web crawlers are increasingly used for focused tasks such as the extraction of data from Wikipedia or the analysis of social networks like last.fm. In these cases, pages are far more uniformly structured than in the general Web and thus crawlers can use the structure of Web pages for more precise data extraction and more expressive analysis.
Franziska von dem Bussche, Klara A. Weiand, Benedikt Linse, Tim Furche, François Bry
WWW2
2010 visKQWL, a visual renderer for a semantic web query language
abstract
KiWi is a semantic Wiki that combines the Wiki philosophy of collaborative content creation with the methods of the Semantic Web in order to enable effective knowledge management.
Andreas Hartl, Klara A. Weiand, François Bry
WWW2
2009 Web Queries: From a Web of Data to a Semantic Web
François Bry, Tim Furche, Klara A. Weiand
WISE3
2007 Formal modelling of L1 and L2 perceptual learning: computational linguistics versus machine learning
abstract
Abstract ∗ In this paper, we evaluate the adequacy of two widely used machine learning algorithms and a computational linguistic proposal to model L2 perceptual development. The three proposals are, in order, Nearest Neighbor, Naive Bayesian and Stochastic OT and the Gradual Learning Algorithm. We compared the three models ’ outputs to those of Spanish learners of Dutch who were asked to categorize synthetic stimuli as one of the 12 Dutch vowels. The empirical results of the human learners show that L2 learners differ significantly from native listeners, but also that their perceptual spaces tend to become more native-like with L2 proficiency. The results of the simulations show that all three algorithms are able to model listeners ’ data to a certain extent but that Stochastic OT and the Gradual Learning Algorithm, i.e. the linguistic model, best reproduces L1 and L2 data. 1.
Paola Escudero, Jelle Kastelein, Klara A. Weiand, R. J. J. H. van Son
INTERSPEECH3