Alexander Mehler

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Alexander Mehler is an author.

Publications

Only those publications related to wikis are shown here.
Title Keyword(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Automatic readability classification of crowd-sourced data based on linguistic and information-theoretic features Enthropy
Evaluation of features
Information transmission
Text readability
Wikipedia
Computacion y Sistemas English 2013 This paper presents a classifier of text readability based on information-theoretic features. The classifier was developed based on a linguistic approach to readability that explores lexical, syntactic and semantic features. For this evaluation we extracted a corpus of 645 articles from Wikipedia together with their quality judgments. We show that information-theoretic features perform as well as their linguistic counterparts even if we explore several linguistic levels at once. 0 0
WikiNect: Towards a gestural writing system for kinetic museum wikis Gestural writing
Gesture-based controlling
HCI
Kinect
Learning
Transient gestures
Wiki
WikiNect
UXeLATE 2012 - Proceedings of the 2012 ACM International Workshop on User Experience in e-Learning and Augmented Technologies in Education, Co-located with ACM Multimedia 2012 English 2012 We introduce WikiNect as a kinetic museum information system that allows museum visitors to give on-site feedback about exhibitions. To this end, WikiNect integrates three approaches to Human-Computer Interaction (HCI): games with a purpose, wiki-based collaborative writing and kinetic text-technologies. Our aim is to develop kinetic technologies as a new paradigm of HCI. They dispense with classical interfaces (e.g., keyboards) in that they build on non-contact modes of communication like gestures or facial expressions as input displays. In this paper, we introduce the notion of gestural writing as a kinetic text-technology that underlies WikiNect to enable museum visitors to communicate their feedback. The basic idea is to explore sequences of gestures that share the semantic expressivity of verbally manifested speech acts. Our task is to identify such gestures that are learnable on-site in the usage scenario of WikiNect. This is done by referring to so-called transient gestures as part of multimodal ensembles, which are candidate gestures of the desired functionality. 0 0
Geography of social ontologies: Testing a variant of the Sapir-Whorf Hypothesis in the context of Wikipedia Automatic language classification
Linguistic networks
Quantitative network analysis
Sapir-Whorf Hypothesis
Social ontologies
Comput. Speech Lang. English 2011 In this article, we test a variant of the {Sapir-Whorf} Hypothesis in the area of complex network theory. This is done by analyzing social ontologies as a new resource for automatic language classification. Our method is to solely explore structural features of social ontologies in order to predict family resemblances of languages used by the corresponding communities to build these ontologies. This approach is based on a reformulation of the {Sapir-Whorf} Hypothesis in terms of distributed cognition. Starting from a corpus of 160 Wikipedia-based social ontologies, we test our variant of the {Sapir-Whorf} Hypothesis by several experiments, and find out that we outperform the corresponding baselines. All in all, the article develops an approach to classify linguistic networks of tens of thousands of vertices by exploring a small range of mathematically well-established topological indices. 0 0
Towards automatic content tagging - Enhanced web services in digital libraries using lexical chaining Digital libraries
Lexical chaining
Lexical network
Social tagging
Topic labelling
Topic structuring
Topic tracking
Wikipedia
WEBIST 2008 - 4th International Conference on Web Information Systems and Technologies, Proceedings English 2008 This paper proposes a web-based application which combines social tagging, enhanced visual representation of a document and the alignment to an open-ended social ontology. More precisely we introduce on the one hand an approach for automatic extraction of document related keywords for indexing and representing document content as an alternative to social tagging. On the other hand a proposal for automatic classification within a social ontology based on the German Wikipedia category taxonomy is proposed. This paper has two main goals: to describe the method of automatic tagging of digital documents and to provide an overview of the algorithmic patterns of lexical chaining that can be applied for topic tracking and -labelling of digital documents. 0 0
Who Is It? Context Sensitive Named Entity and Instance Recognition by Means of Wikipedia English 2008 This paper presents an approach for predicting context sensitive entities exemplified in the domain of person names. Our approach is based on building a weighted context but also a weighted people graph and predicting the context entity by extracting the best fitting sub graph using a spreading activation technique. The results of the experiments show a quite promising F-Measure of 0.99. 0 0
Who is it? Context sensitive named entity and instance recognition by means of Wikipedia Proceedings - 2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008 English 2008 This paper presents an approach for predicting context sensitive entities exemplified in the domain of person names. Our approach is based on building a weighted context but also a weighted people graph and predicting the context entity by extracting the best fitting sub graph using a spreading activation technique. The results of the experiments show a quite promising F-Measure of 0.99. 0 0
Aisles through the category forest;Utilising the Wikipedia Category System for Corpus Building in Machine Learning Category system
Corpus construction
Social tagging
Wikipedia
Webist 2007 - 3rd International Conference on Web Information Systems and Technologies, Proceedings English 2007 The Word Wide Web is a continuous challenge to machine learning. Established approaches have to be enhanced and new methods be developed in order to tackle the problem of finding and organising relevant information. It has often been motivated that semantic classifications of input documents help solving this task. But while approaches of supervised text categorisation perform quite well on genres found in written text, newly evolved genres on the web are much more demanding. In order to successfully develop approaches to web mining, respective corpora are needed. However, the composition of genre- or domain-specific web corpora is still an unsolved problem. It is time consuming to build large corpora of good quality because web pages typically lack reliable meta information. Wikipedia along with similar approaches of collaborative text production offers a way out of this dilemma. We examine how social tagging, as supported by the MediaWiki software, can be utilised as a source of corpus building. Further, we describe a representation format for social ontologies and present the Wikipedia Category Explorer, a tool which supports categorical views to browse through the Wikipedia and to construct domain specific corpora for machine learning. 0 0
Web Corpus Mining by Instance of Wikipedia English 2007 In this paper we present an approach to structure learning in the area of web documents. This is done in order to approach the goal of webgenre tagging in the area of web corpus linguistics. A central outcome of the paper is that purely structure oriented approaches to web document classification provide an information gain which may be utilized in combined approaches of web content and structure analysis. 0 0
Text Linkage in the Wiki Medium - A Comparative Study Wikipedia Proceedings of the EACL 2006 Workshop on New Text - Wikis and blogs and other dynamic text sources, Trento, Italy, April 3-7, pp. 1-8 2006 We analyze four different types of document networks with respect to their small world characteristics. These characteristics allow distinguishing wiki-based systems from citation and more traditional text-based networks augmented by hyperlinks. The study provides evidence that a more appropriate network model is needed which better reflects the specifics of wiki systems. It puts emphasize on their topological differences as a result of wikirelated linking compared to other textbased networks. 0 0