A general approximation framework for direct optimization of information retrieval measures

Recently direct optimization of information retrieval (IR) measures has become a new trend in learning to rank. In this paper, we propose a general framework for direct optimization of IR measures, which enjoys several theoretical advantages. The general framework, which can be used to optimize most IR measures, addresses the task by approximating the IR measures and optimizing the approximated surrogate functions. Theoretical analysis shows that a high approximation accuracy can be achieved by the framework. We take average precision (AP) and normalized discounted cumulated gains (NDCG) as examples to demonstrate how to realize the proposed framework. Experiments on benchmark datasets show that the algorithms deduced from our framework are very effective when compared to existing methods. The empirical results also agree well with the theoretical results obtained in the paper.     

Entity ranking in Wikipedia: utilising categories,links and topic difficulty prediction

Entity ranking has recently emerged as a research field that aims at retrieving entities as answers to a query. Unlike entity extraction where the goal is to tag names of entities in documents, entity ranking is primarily focused on returning a ranked list of relevant entity names for the query. Many approaches to entity ranking have been proposed, and most of them were evaluated on the INEX Wikipedia test collection. In this paper, we describe a system we developed for ranking Wikipedia entities in answer to a query. The entity ranking approach implemented in our system utilises the known categories, the link structure of Wikipedia, as well as the link co-occurrences with the entity examples (when provided) to retrieve relevant entities as answers to the query. We also extend our entity ranking approach by utilising the knowledge of predicted classes of topic difficulty. To predict the topic difficulty, we generate a classifier that uses features extracted from an INEX topic definition to classify the topic into an experimentally pre-determined class. This knowledge is then utilised to dynamically set the optimal values for the retrieval parameters of our entity ranking system. Our experiments demonstrate that the use of categories and the link structure of Wikipedia can significantly improve entity ranking effectiveness, and that topic difficulty prediction is a promising approach that could also be exploited to further improve the entity ranking performance.     

A Look at Global Expansion for e-Books

Forecasts indicate a growing demand for digital content around the world. Converting to digital content can open up countless new revenue possibilities. Adding alternate channels may be worth consideration, but what are the options and what does it take to utilize them effectively? This article explores the opportunities that potentially exist for publishers with content that may be digitized and distributed to global markets. A brief review of the current marketplace is also incorporated, including current players and trends. Finally, an analysis of some of the potential issues, challenges and pitfalls is presented in context of delving into a new international digital content distribution strategy.     

Learning to rank with (a lot of) word features

In this article we present Supervised Semantic Indexing which defines a class of nonlinear (quadratic) models that are discriminatively trained to directly map from the word content in a query-document or document-document pair to a ranking score. Like Latent Semantic Indexing (LSI), our models take account of correlations between words (synonymy, polysemy). However, unlike LSI our models are trained from a supervised signal directly on the ranking task of interest, which we argue is the reason for our superior results. As the query and target texts are modeled separately, our approach is easily generalized to different retrieval tasks, such as cross-language retrieval or online advertising placement. Dealing with models on all pairs of words features is computationally challenging. We propose several improvements to our basic model for addressing this issue, including low rank (but diagonal preserving) representations, correlated feature hashing and sparsification. We provide an empirical study of all these methods on retrieval tasks based on Wikipedia documents as well as an Internet advertisement task. We obtain state-of-the-art performance while providing realistically scalable methods.     

Teacher views on the effects of the change from coursework to controlled assessment in GCSEs

When General Certificates of Secondary Education (GCSEs) were introduced in the late 1980s, coursework was included as a requirement in many subjects. Coursework was intended to help best represent students' attainments, but concerns about various issues (e.g., tasks becoming formulaic, authenticity of student work, workload) led to a review and ultimately to its replacement with “controlled assessments”. This research investigated the effects of this change. A questionnaire was completed by 346 teachers across 6 subjects. Most teachers felt the risks of plagiarism are similar or have reduced. Two thirds of teachers reported that the introduction of controlled assessment has affected the way they teach, and around 60% feel it has affected the nature of the knowledge and skills learnt by students. There are reportedly practical challenges relating to timetabling, student absence, and increased administration. However, over 70% of teachers consider it “important” or “very important” to have some form of internal assessment in their subject.     

Acquisition of Complex Systemic Thinking: Mental Models of Evolution

We investigated the impact of introducing college students to complex adaptive systems on their subsequent mental models of evolution compared to those of students taught in the same manner but with no reference to complex systems. The students' mental models (derived from similarity ratings of 12 evolutionary terms using the pathfinder algorithm) were significantly similar to their teachers' mental models and were correlated to their performance on an essay on evolution. Introducing students to complex systems facilitated their understanding of the mechanism of inheritance, the mechanism of evolution, and the role of chance in evolution.     

Event-Konzepte

In view of processes of individualization and pluralization, the requirements for living in modern societies result in significantly increased complexity of social constructions of reality. Especially for individualized juvenile people new forms of communities are a constitutive feature of social lifestyle progression and rearrangement. Within events a specific type of these juvenile communalities emerges. Based on two different cases, a music festival and an improvisational theater performance, this paper emphasizes a crucial similarity of events: the use of (physical) staging as a social mechanism for integration and distinction. The process of ‘eventization’ (i.e., spectacularization) provides a framework for action, in which emotional as well as mental affiliations constitute.     

Editorial: Kompetenzmodelle zur Erfassung individueller Lernergebnisse und zur Bilanzierung von Bildungsprozessen

This special issue comprises eleven articles from the DFG priority program “Competence Models for Assessing Individual Learning Outcomes and Evaluating Educational Processes”. The special issue aims at showing the priority program’s present state of discussion concerning essential concepts and questions related to the modeling of competencies. The first article describes the structure and research areas of the program and gives an overview on the current state of research. The short articles two to eleven discuss questions and problems which proved to be of particular importance during the work of the priority program in the last years. These articles constitute the result of a workshop of the participating scientists of the priority program in terms of position papers.     

Transferwirkungen künstlerischer Tätigkeiten. Ihre kritische Kommentierung durch eine umfassende Theorie ästhetischer Bildung

Transfer research examines how artistic activities can have an impact outside of the realm of art itself. The article concludes that this research can be carried out in a meaningful way, only within the framework of a comprehensive theory of aesthetic education. This theory would encompass the structural analysis of artistic activity, as well as biographical reports about artistic experiences. The elucidation of the concepts or themes relevant to the theory would include the notion of aesthetic experience, the understanding of immediate, aesthetic experiences, the analysis of artistic processes, and the outcomes of scientifically evaluated applications of aesthetic education.