Ontological Analysis For Description Logics Knowledge Base Debugging

International audienceFormal ontology provides axiomatizations of domain independent principles which, among other applications,can be used to identify modeling errors within a knowledge base. The Ontoclean methodology is probably the best-known illustration of this strategy, but its cost in terms of manual work is often considered dissuasive. This article investigates the applicability of such debugging strategies to Description Logics knowledge bases, showing that even a partial and shallow analysis rapidly performed with a top-level ontology can reveal the presence of violations of common sense, and that the bottleneck, if there is one, may instead reside in the resolution of the resulting inconsistency or incoherence

Mining online diaries for blogger identification

In this paper, we present an investigation of authorship identification on personal blogs or diaries, which are different from other types of text such as essays, emails, or articles based on the text properties. The investigation utilizes couple of intuitive feature sets and studies various parameters that affect the identification performance. Many studies manipulated the problem of authorship identification in manually collected corpora, but only few utilized real data from existing blogs. The complexity of the language model in personal blogs is motivating to identify the correspondent author. The main contribution of this work is at least three folds. Firstly, we utilize the LIWC and MRC feature sets together, which have been developed with Psychology background, for the first time for authorship identification on personal blogs. Secondly, we analyze the effect of various parameters, and feature sets, on the identification performance. This includes the number of authors in the data corpus, the post size or the word count, and the number of posts for each author. Finally, we study applying authorship identification over a limited set of users that have a common personality attributes. This analysis is motivated by the lack of standard or solid recommendations in literature for such task, especially in the domain of personal blogs. The results and evaluation show that the utilized features are compact while their performance is highly comparable with other larger feature sets. The analysis also confirmed the most effective parameters, their ranges in the data corpus, and the usefulness of the common users classifier in improving the performance, for the author identification task

Two-layer classification and distinguished representations of users and documents for grouping and authorship identification

Most studies on authorship identification reported a drop in the identification result when the number of authors exceeds 20-25. In this paper, we introduce a new user representation to address this problem and split classification across two layers. There are at least 3 novelties in this paper. First, the two-layer approach allows applying authorship identification over larger number of authors (tested over 100 authors), and it is extendable. The authors are divided into groups that contain smaller number of authors. Given an anonymous document, the primary layer detects the group to which the document belongs. Then, the secondary layer determines the particular author inside the selected group. In order to extract the groups linking similar authors, clustering is applied over users rather than documents. Hence, the second novelty of this paper is introducing a new user representation that is different from document representation. Without the proposed user representation, the clustering over documents will result in documents of author(s) distributed over several clusters, instead of a single cluster membership for each author. Third, the extracted clusters are descriptive and meaningful of their users as the dimensions have psychological backgrounds. For authorship identification, the documents are labelled with the extracted groups and fed into machine learning to build classification models that predicts the group and author of a given document. The results show that the documents are highly correlated with the extracted corresponding groups, and the proposed model can be accurately trained to determine the group and the author identity

Comparing automatically detected reflective texts with human judgements

This paper reports on the descriptive results of an experiment comparing automatically detected reflective and not-reflective texts against human judgements. Based on the theory of reflective writing assessment and their operationalisation five elements of reflection were defined. For each element of reflection a set of indicators was developed, which automatically annotate texts regarding reflection based on the parameterisation with authoritative texts. Using a large blog corpus 149 texts were retrieved, which were either annotated as reflective or notreflective. An online survey was then used to gather human judgements for these texts. These two data sets were used to compare the quality of the reflection detection algorithm with human judgments. The analysis indicates the expected difference between reflective and not reflective texts

E-mindfulness – the growing importance of facilitating tourists’ connections to the present moment

The purpose of this paper is to introduce e-mindfulness as a tourism trend. Mindfulness meditation is becoming increasingly mainstream, which is reflected in a rapidly growing number of related technology applications. Such technology-assisted mindfulness is typically referred to as e-mindfulness. The e-mindfulness trend creates opportunities for the tourism industry but also implies changed consumer perspectives on tourist experiences. Design/methodology/approach: The paper is based on a general review of academic literature, news reports and online resources regarding the offerings of related technologies. Findings: Implications of e-mindfulness for consumers, tourism service providers and designers of future tourism experiences are outlined. Originality/value: This is the first paper to conceptualize e-mindfulness as a tourism trend