Neural Domain Adaptation for Biomedical Question Answering

Factoid question answering (QA) has recently benefited from the development of deep learning (DL) systems. Neural network models outperform traditional approaches in domains where large datasets exist, such as SQuAD (ca. 100,000 questions) for Wikipedia articles. However, these systems have not yet been applied to QA in more specific domains, such as biomedicine, because datasets are generally too small to train a DL system from scratch. For example, the BioASQ dataset for biomedical QA comprises less then 900 factoid (single answer) and list (multiple answers) QA instances. In this work, we adapt a neural QA system trained on a large open-domain dataset (SQuAD, source) to a biomedical dataset (BioASQ, target) by employing various transfer learning techniques. Our network architecture is based on a state-of-the-art QA system, extended with biomedical word embeddings and a novel mechanism to answer list questions. In contrast to existing biomedical QA systems, our system does not rely on domain-specific ontologies, parsers or entity taggers, which are expensive to create. Despite this fact, our systems achieve state-of-the-art results on factoid questions and competitive results on list questions

Revamping question answering with a semantic approach over world knowledge

Classic textual question answering (QA) approaches that rely on statistical keyword relevance scoring without exploiting semantic content are useful to a certain extent, but are limited to questions answered by a small text excerpt. With the maturation of Wikipedia and with upcoming projects like DBpedia, we feel that nowadays QA can adopt a deeper, semantic approach to the task, where answers can be inferred using knowledge bases to overcome the limitations of textual QA approaches. In GikiCLEF, a QA-flavoured evaluation task, the best performing systems followed a semantic approach. In this paper, we present our motivations for preferring semantic approaches to QA over textual approaches, with Wikipedia serving as a raw knowledge source

Australian software developers embrace quality Assurance Certification

[Abstract]: This paper details a research project undertaken to assess the extent of adoption of quality assurance (QA) certification by Australian software developers. A brief history of government QA policy, the catalyst in the sudden interest in certification, is included. Primary data for the study were gathered from a survey of 1,000 Australian software developers, and were used to determine the extent of adoption of QA certification by Australian developers, their organisational characteristics, capability maturity and perceptions regarding the value of QA certification. Secondary data from the JAS-ANZ register of certified organisations enabled validation of survey responses and extrapolation of QA certification adoption. Major findings of the study revealed that 11 percent of respondents are certified to ISO 9001 or AS 3563, seven percent are in progress and 21 percent plan to adopt QA certification. It also revealed that specialist developers are adopting QA certification at twice the rate of in-house developers. Other factors found to be associated with adoption of QA certification are large development groups, developers with government or overseas clients, organisations with whole- or part-foreign ownership, and organisations undertaking corporate TQM initiatives. From the findings, detailed implications are drawn for managers and policy analysts

Design of Quantum Annealing Machine for Prime Factoring

We propose a prime factoring machine operated in a frame work of quantum annealing (QA). The idea is inverse operation of a quantum-mechanically reversible multiplier implemented with QA-based Boolean logic circuits. We designed the QA machine on an application-specific-annealing-computing architecture which efficiently increases available hardware budgets at the cost of restricted functionality. The circuits are to be implemented and fabricated by using superconducting integrated circuit technology. We propose a three-dimensional packaging scheme of a qubit-chip / interposer / package-substrate structure for realizing practically-large scale QA systems.Comment: 3 pages, 6 figures, to appear in IEEE Xplore Conference Proceedings of the 16th International Superconductive Electronics Conference (ISEC 2017