Text classification, whether by topic or genre, is an important task that contributes to text extraction, retrieval, summarization and question answering. In this paper we present a new pairwise ensemble approach, which uses pairwise Support Vector Machine (SVM) classifiers as base classifiers and “input-dependent latent variable” method for model combination. This new approach better captures ...

This article constitutes a critique from the inside of constructivist pedagogy. It begins with a short history of constructivist pedagogy and its relationship to constructivist learning theory. It then addresses four issues in the ways in which constructivist pedagogy are being approached in research and practice. The first issue recommends more of a research focus on student learning in classr...

This study presents the concept of innovation pedagogy, which is a pedagogical approach developed for the universities of applied sciences. Innovation pedagogy emphasises efficient learning and the institution’s external impact on regional development. It is based on customer-oriented and multi-field needs of working life; integrates applied research and development and entrepreneurship with ed...

This paper summarizes our contribution (team DBIS) to the AcousticBrainz Genre Task: Content-based music genre recognition from multiple sources as part of MediaEval 2017. We utilize a hierarchical set of multilabel classifiers to predict genres and subgenres and rely on a voting scheme to predict labels across datasets.

In this paper we present a cross-genre study on word order variation in Italian based on automatically dependency– parsed corpora. A comparative analysis focused on dependency direction and dependency distance for major constituents in the sentence is carried out in order to assess the influence of both textual genre and linguistic complexity on the distribution of phenonemena of syntactic mark...

This paper presents experimentson classifyingweb pages by genre. Firstly, a corpus of 1 539 manually labeled web pages was prepared. Secondly, 502 genre features were selected based on the literature and the observation of the corpus. Thirdly, these features were extracted from the corpus to obtain a data set. Finally, two machine learning algorithms, one for induction of decision trees (J48) a...

In the era of e-learning, student-centered approaches and constructivists learning environments are critical success factors. The inherent interactivity of the Internet and the emotional engagement of story can lead to transformative learning experiences in media rich environments. This paper focuses on Web-Based Transmedia Storytelling Edutainment as critical-creative pedagogy in higher e-educ...

This paper describes our participation in Genre Tagging Task @ MediaEval 2011, which aims at predicting the Genre of Internet videos. We propose a method that extracts low dimensional feature space based on text, audio and video information. In the best configuration, our system yields a 0.56 MAP (Mean Average Precision) on the test corpus.

How to characterize a literary genre is a much debated problem, which can be approached with useful results by combining models drawn from both Literary Theory and Computer Science. Once a genre is specified with some rigour in a constructive way, it becomes possible not only to determine whether a given plot is a legitimate representative of the genre, but also to generate such plots, an abili...