Complex Knowledge Base Question Answering: A Survey

Knowledge base question answering (KBQA) aims to answer a question over a knowledge base (KB). Early studies mainly focused on answering simple questions over KBs and achieved great success. However, their performance on complex questions is still far from satisfactory. Therefore, in recent years, researchers propose a large number of novel methods, which looked into the challenges of answering complex questions. In this survey, we review recent advances on KBQA with the focus on solving complex questions, which usually contain multiple subjects, express compound relations, or involve numerical operations. In detail, we begin with introducing the complex KBQA task and relevant background. Then, we describe benchmark datasets for complex KBQA task and introduce the construction process of these datasets. Next, we present two mainstream categories of methods for complex KBQA, namely semantic parsing-based (SP-based) methods and information retrieval-based (IR-based) methods. Specifically, we illustrate their procedures with flow designs and discuss their major differences and similarities. After that, we summarize the challenges that these two categories of methods encounter when answering complex questions, and explicate advanced solutions and techniques used in existing work. Finally, we conclude and discuss several promising directions related to complex KBQA for future research.Comment: 20 pages, 4 tables, 7 figures. arXiv admin note: text overlap with arXiv:2105.1164

Any tool works if you are using the language: the role of knowledge in ICT integration in a Johannesburg private school

A research report submitted to the Wits School of Education, Faculty of Humanities, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements of the degree of Master of Education by combination of coursework and research. Johannesburg 2016Increasingly teachers are expected to integrate ICTs into their teaching practice. Recent studies have focused on the role played by teachers’ technological pedagogical content knowledge in explaining how they exploit the affordances offered by the new digital technologies, and yet the pace of integration has been far slower than expected. Education is founded on the business of knowledge, and yet there is a knowledge blindness in educational research. This study tries to discern what effect subject specialization and knowledge has on teacher’s adoption of ICTs into their pedagogical practice, using the framework of Legitimation Code Theory, in particular semantic waves. Seeing ICT practices as affording both knower and knowledge practices, and as affording gravitation or levitation allows us to start to unpack further how the forms knowledge takes influences decisions around ICT adoption.MT201

Households’ Indebtedness and Financial Fragility

The paper studies the determinants of international differences in household indebtedness, and inquires whether indebtedness is associated with increased “financial fragility”, as measured by the sensitivity of household arrears and insolvencies to macroeconomic shocks. It also investigates whether financial fragility is affected by institutional factors, such as information sharing arrangements, judicial efficiency and individual bankruptcy regulation. We address these issues by tapping three data sets: (i) cross-country data on household indebtedness; (ii) European panel data for households lending and arrears; and (iii) time series data for household lending and insolvencies in the U.K., the U.S.A. and Germany. Overall, the analysis underscores the importance of institutional arrangements in determining the size and fragility of household credit markets.household debt, financial fragility, arrears, insolvency, information sharing, judicial efficiency, bankruptcy law