A Holistic Approach to OLAP Sessions Composition: The Falseto Experience

International audienceOLAP is the main paradigm for flexible and effective exploration of multidimensional cubes in data warehouses. During an OLAP session the user analyzes the results of a query and determines a new query that will give her a better understanding of information. Given the huge size of the data space, this exploration process is often tedious and may leave the user disoriented and frustrated. This paper presents an OLAP tool 1 named Falseto (Former AnalyticaL Sessions for lEss Tedious Olap), that is meant to assist query and session composition, by letting the user summarize, browse, query, and reuse former analytical sessions. Falseto's implementation on top of a formal framework is detailed. We also report the experiments we run to obtain and analyze real OLAP sessions and assess Falseto with them. Finally, we discuss how Falseto can be seen as a starting point for bridging OLAP with exploratory search, a search paradigm centered on the user and the evolution of her knowledge

Identifying Structure in Introductory Topology: Diagrams, Examples, and Gestures

Despite the prevalence of research in calculus, linear algebra, abstract algebra, and analysis in undergraduate mathematics, the teaching and learning of general topology is a largely unexplored area of research. Although enrollment in courses like linear algebra is often higher than that of topology, the study of students’ learning and understanding of topology is of great significance to the Research in Undergraduate Mathematics Education (RUME) community. Courses in topology present many students with their first experience in axiomatic reasoning and explicit interactions with mathematical structure, itself. I present a thorough case study of Stacey, an undergraduate taking a first course in undergraduate topology. Through the lenses of mathematical structuralism, constructivism, embodied cognition, and commognition, I investigated Stacey’s proving behaviors. Papers 1, 2, and 3 present a top-down description of Stacey’s behaviors as she sought to identify the key ideas of proofs in general topology. In Paper 1, I described Stacey’s proving behaviors using vocabulary borrowed from the literature on problem solving and showed that she used diagrams to arrive at the key idea. In Paper 2, I observed that Stacey seldom produced specific examples, but she reasoned about her diagrams as examples and manipulation of these examples led her to the key ideas of several proofs and to identify appropriate counterexamples when necessary. In Paper 3, I used the theories of embodied cognition and commognition to argue that Stacey’s use of diagrams to ground abstract structures in the external world gave her the ability to manipulate those structures spatially, ultimately leading her to the key idea. These three papers are three perspectives on the same theme, each digging more deeply than the one before. Stacey’s behaviors in Papers 1, 2, and 3 describe her search for and investigation of abstract mathematical structures. Stacey’s recognition of structure and her ability to work with it helped her to succeed in writing proofs. I conclude this dissertation with suggestions for teaching, including incorporation of the theories of embodied cognition and commognition, as well as directions for future research

An Alternative Approach to Measuring Opportunity-to-Learn in High School Classes

The Opportunity-to-Learn framework has provided policymakers and researchers a means to develop strategies to measure classroom practices. In particular, the measure of the delivered content has been shown to be a good predictor of student achievement on tests. The method presented in this article uses classroom artifacts as the main data source to determine the attention teachers give to various content in the curriculum. The number of treatments that address set learning outcomes was the unit of measurement employed in this method. The article illustrates how this method was used to describe content delivery and how content emphasis exposed the differences between two teachers following the same prescribed syllabus. This method is best applied at the secondary school level to measure one component of the delivered curriculum. Finally, the limitations and potential of this method are discussed for use in research and for school improvement.Les décideurs et les chercheurs ont eu recours au cadre « Opportunity to Learn » (occasion d’apprentissage) dans le développement de stratégies pour mesurer les pratiques en salle de classe. En fait, la mesure du contenu fourni aux élèves s’est avérée être un bon prédicteur de la performance des élèves aux examens. Cet article présente une méthode s’appuyant sur les artéfacts de la salle de classe comme source principale de données et visant l’évaluation de l’attention qu’accordent les enseignants à divers contenus du programme d’études. Le nombre d’interventions visant des résultats d’apprentissage déterminés a constitué l’unité de mesure. L’article démontre, d’une part, l’emploi de cette méthode pour décrire la prestation de contenu et d’autre part, comment le fait de porter attention au contenu fait ressortir des différences entre deux enseignants qui suivent le même syllabus. Cette méthode s’applique le mieux au niveau secondaire pour mesurer une composante du programme d’études. L’article termine par une discussion des limites et du potentiel de cette méthode dans le contexte de la recherche et de l’amélioration du rendement scolaire

Qualitative Analysis of the SQLShare Workload for Session Segmentation

International audienceThis paper presents an ongoing work aiming at better understanding the workload of SQLShare [9]. SQLShare is database-as-a-service platform targeting scientists and data scientists with minimal database experience, whose workload was made available to the research community. According to the authors of [9], this workload is the only one containing primarily ad-hoc handwritten queries over user-uploaded datasets. We analyzed this workload by extracting features that characterize SQL queries and we show how to use these features to separate sequences of SQL queries into meaningful sessions. We ran a few test over various query workloads to validate empirically our approach

Symbolic-numeric interface: A review

A survey of the use of a combination of symbolic and numerical calculations is presented. Symbolic calculations primarily refer to the computer processing of procedures from classical algebra, analysis, and calculus. Numerical calculations refer to both numerical mathematics research and scientific computation. This survey is intended to point out a large number of problem areas where a cooperation of symbolic and numerical methods is likely to bear many fruits. These areas include such classical operations as differentiation and integration, such diverse activities as function approximations and qualitative analysis, and such contemporary topics as finite element calculations and computation complexity. It is contended that other less obvious topics such as the fast Fourier transform, linear algebra, nonlinear analysis and error analysis would also benefit from a synergistic approach

Use of Knowledge Technologies for Presentation of Bulgarian Folklore Heritage Semantics

Preserving and presenting the Bulgarian folklore heritage is a long-term commitment of scholars and researchers working in many areas. This article presents ontological model of the Bulgarian folklore knowledge, exploring knowledge technologies for presenting the semantics of the phenomena of our traditional culture. This model is a step to the development of the digital library for the “Bulgarian Folklore Heritage” virtual exposition which is a part of the “Knowledge Technologies for Creation of Digital Presentation and Significant Repositories of Folklore Heritage” project

Leveraging query logs for user-centric OLAP

OLAP (On-Line Analytical Processing), the process of efficiently enabling common analytical operations on the multidimensional view of data, is a corner stone of Business Intelligence.While OLAP is now a mature, efficiently implemented technology, very little attention has been paid to the effectiveness of the analysis and the user-friendliness of this technology, often considered tedious of use.This dissertation is a contribution to developing user-centric OLAP, focusing on the use of former queries logged by an OLAP server to enhance subsequent analyses. It shows how logs of OLAP queries can be modeled, constructed, manipulated, compared, and finally leveraged for personalization and recommendation.Logs are modeled as sets of analytical sessions, sessions being modeled as sequences of OLAP queries. Three main approaches are presented for modeling queries: as unevaluated collections of fragments (e.g., group by sets, sets of selection predicates, sets of measures), as sets of references obtained by partially evaluating the query over dimensions, or as query answers. Such logs can be constructed even from sets of SQL query expressions, by translating these expressions into a multidimensional algebra, and bridging the translations to detect analytical sessions. Logs can be searched, filtered, compared, combined, modified and summarized with a language inspired by the relational algebra and parametrized by binary relations over sessions. In particular, these relations can be specialization relations or based on similarity measures tailored for OLAP queries and analytical sessions. Logs can be mined for various hidden knowledge, that, depending on the query model used, accurately represents the user behavior extracted.This knowledge includes simple preferences, navigational habits and discoveries made during former explorations,and can be it used in various query personalization or query recommendation approaches.Such approaches vary in terms of formulation effort, proactiveness, prescriptiveness and expressive power:query personalization, i.e., coping with a current query too few or too many results, can use dedicated operators for expressing preferences, or be based on query expansion;query recommendation, i.e., suggesting queries to pursue an analytical session,can be based on information extracted from the current state of the database and the query, or be purely history based, i.e., leveraging the query log.While they can be immediately integrated into a complete architecture for User-Centric Query Answering in data warehouses, the models and approaches introduced in this dissertation can also be seen as a starting point for assessing the effectiveness of analytical sessions, with the ultimate goal to enhance the overall decision making process